The Data Science Course Complete Data Science Bootcamp 2025 Dec 2024

The Data Science Course Complete Data Science Bootcamp 2025 Dec 2024

Name	The Data Science Course Complete Data Science Bootcamp 2025 (Dec-2024)	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	9.9 GB
Total Files	1493
Last Seen	2025-07-18 00:17
Hash	9A03EAE6885C6EACA8F516880C02705743F8EACA

/01. Part 1 Introduction/
01. A Practical Example What You Will Learn in This Course.mp4	11.3 MB
01. A Practical Example What You Will Learn in This Course.vtt	7.0 KB
02. What Does the Course Cover.mp4	10.0 MB
02. What Does the Course Cover.vtt	5.6 KB
03. Download All Resources and Important FAQ.html	21.9 KB
/assets/
03. FAQ-The-Data-Science-Course.pdf	313.4 KB
/02. The Field of Data Science - The Various Data Science Disciplines/
01. Data Science and Business Buzzwords Why are there so Many.mp4	16.3 MB
01. Data Science and Business Buzzwords Why are there so Many.vtt	7.5 KB
02. What is the difference between Analysis and Analytics.mp4	11.7 MB
02. What is the difference between Analysis and Analytics.vtt	5.2 KB
03. Business Analytics, Data Analytics, and Data Science An Introduction.mp4	15.3 MB
03. Business Analytics, Data Analytics, and Data Science An Introduction.vtt	9.9 KB
04. Continuing with BI, ML, and AI.mp4	49.9 MB
04. Continuing with BI, ML, and AI.vtt	13.4 KB
05. Traditional AI vs. Generative AI.mp4	25.7 MB
05. Traditional AI vs. Generative AI.vtt	7.1 KB
06. More Examples of Generative AI.mp4	32.0 MB
06. More Examples of Generative AI.vtt	7.0 KB
07. A Breakdown of our Data Science Infographic.mp4	47.6 MB
07. A Breakdown of our Data Science Infographic.vtt	5.2 KB
/assets/
03. 365-DataScience-Diagram.pdf	330.8 KB
04. 365-DataScience-Diagram.pdf	330.8 KB
04. 365-DataScience.png	7.3 MB
07. 365-DataScience.png	7.3 MB
/03. The Field of Data Science - Connecting the Data Science Disciplines/
01. Applying Traditional Data, Big Data, BI, Traditional Data Science and ML.mp4	87.6 MB
01. Applying Traditional Data, Big Data, BI, Traditional Data Science and ML.vtt	9.5 KB
/04. The Field of Data Science - The Benefits of Each Discipline/
01. The Reason Behind These Disciplines.mp4	49.0 MB
01. The Reason Behind These Disciplines.vtt	6.7 KB
/05. The Field of Data Science - Popular Data Science Techniques/
01. Techniques for Working with Traditional Data.mp4	112.4 MB
01. Techniques for Working with Traditional Data.vtt	11.2 KB
02. Real Life Examples of Traditional Data.mp4	19.3 MB
02. Real Life Examples of Traditional Data.vtt	2.4 KB
03. Techniques for Working with Big Data.mp4	65.1 MB
03. Techniques for Working with Big Data.vtt	6.0 KB
04. Real Life Examples of Big Data.mp4	13.7 MB
04. Real Life Examples of Big Data.vtt	1.9 KB
05. Business Intelligence (BI) Techniques.mp4	55.5 MB
05. Business Intelligence (BI) Techniques.vtt	9.0 KB
06. Real Life Examples of Business Intelligence (BI).mp4	25.8 MB
06. Real Life Examples of Business Intelligence (BI).vtt	2.3 KB
07. Techniques for Working with Traditional Methods.mp4	79.7 MB
07. Techniques for Working with Traditional Methods.vtt	11.8 KB
08. Real Life Examples of Traditional Methods.mp4	38.5 MB
08. Real Life Examples of Traditional Methods.vtt	5.5 KB
09. Machine Learning (ML) Techniques.mp4	51.8 MB
09. Machine Learning (ML) Techniques.vtt	9.5 KB
10. Types of Machine Learning.mp4	72.8 MB
10. Types of Machine Learning.vtt	11.2 KB
11. Evolution and Latest Trends of Machine Learning (ML).mp4	28.7 MB
11. Evolution and Latest Trends of Machine Learning (ML).vtt	7.9 KB
12. Real Life Examples of Machine Learning (ML).mp4	29.1 MB
12. Real Life Examples of Machine Learning (ML).vtt	3.1 KB
/06. The Field of Data Science - Popular Data Science Tools/
01. Necessary Programming Languages and Software Used in Data Science.mp4	86.4 MB
01. Necessary Programming Languages and Software Used in Data Science.vtt	8.2 KB
/07. The Field of Data Science - Careers in Data Science/
01. Finding the Job - What to Expect and What to Look for.mp4	42.0 MB
01. Finding the Job - What to Expect and What to Look for.vtt	4.8 KB
/08. The Field of Data Science - Debunking Common Misconceptions/
01. Debunking Common Misconceptions.mp4	61.7 MB
01. Debunking Common Misconceptions.vtt	5.7 KB
/09. Part 2 Probability/
01. The Basic Probability Formula.mp4	30.8 MB
01. The Basic Probability Formula.vtt	9.2 KB
02. Computing Expected Values.mp4	47.9 MB
02. Computing Expected Values.vtt	7.1 KB
03. Frequency.mp4	39.2 MB
03. Frequency.vtt	7.1 KB
04. Events and Their Complements.mp4	27.1 MB
04. Events and Their Complements.vtt	7.3 KB
/assets/
01. Course-Notes-Basic-Probability.pdf	380.0 KB
/10. Probability - Combinatorics/
01. Fundamentals of Combinatorics.mp4	6.2 MB
01. Fundamentals of Combinatorics.vtt	1.5 KB
02. Permutations and How to Use Them.mp4	18.4 MB
02. Permutations and How to Use Them.vtt	4.5 KB
03. Simple Operations with Factorials.mp4	11.0 MB
03. Simple Operations with Factorials.vtt	3.5 KB
04. Solving Variations with Repetition.mp4	14.6 MB
04. Solving Variations with Repetition.vtt	3.8 KB
05. Solving Variations without Repetition.mp4	19.1 MB
05. Solving Variations without Repetition.vtt	5.1 KB
06. Solving Combinations.mp4	24.8 MB
06. Solving Combinations.vtt	6.2 KB
07. Symmetry of Combinations.mp4	14.4 MB
07. Symmetry of Combinations.vtt	4.6 KB
08. Solving Combinations with Separate Sample Spaces.mp4	21.3 MB
08. Solving Combinations with Separate Sample Spaces.vtt	4.2 KB
09. Combinatorics in Real-Life The Lottery.mp4	17.2 MB
09. Combinatorics in Real-Life The Lottery.vtt	4.3 KB
10. A Recap of Combinatorics.mp4	12.7 MB
10. A Recap of Combinatorics.vtt	3.9 KB
11. A Practical Example of Combinatorics.mp4	84.6 MB
11. A Practical Example of Combinatorics.vtt	15.5 KB
/assets/
01. Course-Notes-Combinatorics.pdf	231.5 KB
06. Combinations-With-Repetition.pdf	212.4 KB
07. Symmetry-Explained.pdf	87.1 KB
11. Additional-Exercises-Combinatorics-Solutions.pdf	251.6 KB
11. Additional-Exercises-Combinatorics.pdf	109.1 KB
/11. Probability - Bayesian Inference/
01. Sets and Events.mp4	18.5 MB
01. Sets and Events.vtt	5.6 KB
02. Ways Sets Can Interact.mp4	11.9 MB
02. Ways Sets Can Interact.vtt	4.7 KB
03. Intersection of Sets.mp4	11.6 MB
03. Intersection of Sets.vtt	2.7 KB
04. Union of Sets.mp4	25.4 MB
04. Union of Sets.vtt	6.4 KB
05. Mutually Exclusive Sets.mp4	11.1 MB
05. Mutually Exclusive Sets.vtt	2.8 KB
06. Dependence and Independence of Sets.mp4	15.6 MB
06. Dependence and Independence of Sets.vtt	3.6 KB
07. The Conditional Probability Formula.mp4	21.0 MB
07. The Conditional Probability Formula.vtt	6.0 KB
08. The Law of Total Probability.mp4	14.9 MB
08. The Law of Total Probability.vtt	4.0 KB
09. The Additive Rule.mp4	11.6 MB
09. The Additive Rule.vtt	2.7 KB
10. The Multiplication Law.mp4	21.2 MB
10. The Multiplication Law.vtt	4.8 KB
11. Bayes' Law.mp4	22.4 MB
11. Bayes' Law.vtt	7.9 KB
12. A Practical Example of Bayesian Inference.mp4	146.0 MB
12. A Practical Example of Bayesian Inference.vtt	20.6 KB
/assets/
01. Course-Notes-Bayesian-Inference.pdf	395.3 KB
12. Bayesian-Homework-Solutions.pdf	31.1 KB
12. Bayesian-Homework.pdf	27.9 KB
12. CDS-2017-2018-Hamilton.pdf	865.6 KB
/12. Probability - Distributions/
01. Fundamentals of Probability Distributions.mp4	20.4 MB
01. Fundamentals of Probability Distributions.vtt	8.6 KB
02. Types of Probability Distributions.mp4	37.3 MB
02. Types of Probability Distributions.vtt	10.7 KB
03. Characteristics of Discrete Distributions.mp4	9.9 MB
03. Characteristics of Discrete Distributions.vtt	2.6 KB
04. Discrete Distributions The Uniform Distribution.mp4	10.8 MB
04. Discrete Distributions The Uniform Distribution.vtt	3.0 KB
05. Discrete Distributions The Bernoulli Distribution.mp4	15.9 MB
05. Discrete Distributions The Bernoulli Distribution.vtt	5.3 KB
06. Discrete Distributions The Binomial Distribution.mp4	32.1 MB
06. Discrete Distributions The Binomial Distribution.vtt	9.0 KB
07. Discrete Distributions The Poisson Distribution.mp4	25.1 MB
07. Discrete Distributions The Poisson Distribution.vtt	7.4 KB
08. Characteristics of Continuous Distributions.mp4	22.3 MB
08. Characteristics of Continuous Distributions.vtt	9.4 KB
09. Continuous Distributions The Normal Distribution.mp4	21.0 MB
09. Continuous Distributions The Normal Distribution.vtt	5.2 KB
10. Continuous Distributions The Standard Normal Distribution.mp4	22.1 MB
10. Continuous Distributions The Standard Normal Distribution.vtt	5.9 KB
11. Continuous Distributions The Students' T Distribution.mp4	9.7 MB
11. Continuous Distributions The Students' T Distribution.vtt	3.3 KB
12. Continuous Distributions The Chi-Squared Distribution.mp4	11.7 MB
12. Continuous Distributions The Chi-Squared Distribution.vtt	3.1 KB
13. Continuous Distributions The Exponential Distribution.mp4	16.8 MB
13. Continuous Distributions The Exponential Distribution.vtt	4.6 KB
14. Continuous Distributions The Logistic Distribution.mp4	17.0 MB
14. Continuous Distributions The Logistic Distribution.vtt	5.5 KB
15. A Practical Example of Probability Distributions.mp4	145.0 MB
15. A Practical Example of Probability Distributions.vtt	21.6 KB
/assets/
01. Course-Notes-Probability-Distributions.pdf	475.1 KB
07. Poisson-Expected-Value-and-Variance.pdf	149.5 KB
08. Solving-Integrals.pdf	352.1 KB
09. Normal-Distribution-Exp-and-Var.pdf	147.5 KB
15. Customers-Membership-post.xlsx	16.0 KB
15. Customers-Membership.xlsx	9.9 KB
15. Daily-Views-post.xlsx	20.7 KB
15. Daily-Views.xlsx	9.8 KB
15. FIFA19-post.csv	9.1 MB
15. FIFA19.csv	9.1 MB
/13. Probability - Probability in Other Fields/
01. Probability in Finance.mp4	42.3 MB
01. Probability in Finance.vtt	10.3 KB
02. Probability in Statistics.mp4	33.1 MB
02. Probability in Statistics.vtt	9.3 KB
03. Probability in Data Science.mp4	14.9 MB
03. Probability in Data Science.vtt	7.3 KB
/assets/
01. Probability-in-Finance-Homework.pdf	113.3 KB
01. Probability-in-Finance-Solutions.pdf	188.9 KB
03. Probability-Cheat-Sheet.pdf	328.0 KB
/14. Part 3 Statistics/
01. Population and Sample.mp4	36.8 MB
01. Population and Sample.vtt	6.0 KB
/assets/
01. Course-notes-descriptive-statistics.pdf	493.8 KB
01. Statistics-Glossary.xlsx	20.8 KB
/15. Statistics - Descriptive Statistics/
01. Types of Data.mp4	45.3 MB
01. Types of Data.vtt	6.0 KB
02. Levels of Measurement.mp4	33.8 MB
02. Levels of Measurement.vtt	4.9 KB
03. Categorical Variables - Visualization Techniques.mp4	28.8 MB
03. Categorical Variables - Visualization Techniques.vtt	6.9 KB
04. Categorical Variables Exercise.html	0.1 KB
05. Numerical Variables - Frequency Distribution Table.mp4	18.6 MB
05. Numerical Variables - Frequency Distribution Table.vtt	4.6 KB
06. Numerical Variables Exercise.html	0.1 KB
07. The Histogram.mp4	10.0 MB
07. The Histogram.vtt	3.4 KB
08. Histogram Exercise.html	0.1 KB
09. Cross Tables and Scatter Plots.mp4	20.7 MB
09. Cross Tables and Scatter Plots.vtt	7.1 KB
10. Cross Tables and Scatter Plots Exercise.html	0.1 KB
11. Mean, median and mode.mp4	25.7 MB
11. Mean, median and mode.vtt	6.1 KB
12. Mean, Median and Mode Exercise.html	0.1 KB
13. Skewness.mp4	14.0 MB
13. Skewness.vtt	3.8 KB
14. Skewness Exercise.html	0.1 KB
15. Variance.mp4	24.7 MB
15. Variance.vtt	8.4 KB
16. Variance Exercise.html	0.5 KB
17. Standard Deviation and Coefficient of Variation.mp4	21.1 MB
17. Standard Deviation and Coefficient of Variation.vtt	6.5 KB
18. Standard Deviation and Coefficient of Variation Exercise.html	0.1 KB
19. Covariance.mp4	19.3 MB
19. Covariance.vtt	5.2 KB
20. Covariance Exercise.html	0.1 KB
21. Correlation Coefficient.mp4	20.3 MB
21. Correlation Coefficient.vtt	5.1 KB
22. Correlation Coefficient Exercise.html	0.1 KB
/assets/
01. Course-notes-descriptive-statistics.pdf	493.8 KB
01. Glossary.xlsx	20.4 KB
03. 2.3.Categorical-variables.Visualization-techniques-lesson.xlsx	31.5 KB
04. 2.3.Categorical-variables.Visualization-techniques-exercise-solution.xlsx	42.1 KB
04. 2.3.Categorical-variables.Visualization-techniques-exercise.xlsx	15.6 KB
04. Statistics-PDF-with-Excel-Solutions-that-dont-visualize-properly.pdf	296.1 KB
05. 2.4.Numerical-variables.Frequency-distribution-table-lesson.xlsx	11.7 KB
06. 2.4.Numerical-variables.Frequency-distribution-table-exercise-solution.xlsx	13.5 KB
07. 2.5.The-Histogram-lesson.xlsx	19.1 KB
08. 2.5.The-Histogram-exercise-solution.xlsx	17.5 KB
08. 2.5.The-Histogram-exercise.xlsx	15.9 KB
08. Statistics-PDF-with-Excel-Solutions-that-dont-visualize-properly.pdf	296.1 KB
09. 2.6.Cross-table-and-scatter-plot.xlsx	26.7 KB
10. 2.6.Cross-table-and-scatter-plot-exercise-solution.xlsx	41.4 KB
10. 2.6.Cross-table-and-scatter-plot-exercise.xlsx	16.7 KB
11. 2.7.Mean-median-and-mode-lesson.xlsx	10.7 KB
12. 2.7.Mean-median-and-mode-exercise-solution.xlsx	11.6 KB
12. 2.7.Mean-median-and-mode-exercise.xlsx	11.1 KB
13. 2.8.Skewness-lesson.xlsx	35.5 KB
14. 2.8.Skewness-exercise-solution.xlsx	20.3 KB
14. 2.8.Skewness-exercise.xlsx	9.7 KB
15. 2.9.Variance-lesson.xlsx	10.3 KB
16. 2.9.Variance-exercise-solution.xlsx	11.3 KB
16. 2.9.Variance-exercise.xlsx	11.1 KB
17. 2.10.Standard-deviation-and-coefficient-of-variation-lesson.xlsx	11.2 KB
18. 2.10.Standard-deviation-and-coefficient-of-variation-exercise-solution.xlsx	12.9 KB
18. 2.10.Standard-deviation-and-coefficient-of-variation-exercise.xlsx	11.9 KB
19. 2.11.Covariance-lesson.xlsx	25.5 KB
20. 2.11.Covariance-exercise-solution.xlsx	30.2 KB
20. 2.11.Covariance-exercise.xlsx	20.7 KB
22. 2.12.Correlation-exercise-solution.xlsx	30.2 KB
22. 2.12.Correlation-exercise.xlsx	30.0 KB
/16. Statistics - Practical Example Descriptive Statistics/
01. Practical Example Descriptive Statistics.mp4	136.9 MB
01. Practical Example Descriptive Statistics.vtt	21.5 KB
02. Practical Example Descriptive Statistics Exercise.html	0.1 KB
/assets/
01. 2.13.Practical-example.Descriptive-statistics-lesson.xlsx	150.0 KB
02. 2.13.Practical-example.Descriptive-statistics-exercise-solution.xlsx	149.9 KB
02. 2.13.Practical-example.Descriptive-statistics-exercise.xlsx	123.2 KB
/17. Statistics - Inferential Statistics Fundamentals/
01. Introduction.mp4	3.2 MB
01. Introduction.vtt	1.7 KB
02. What is a Distribution.mp4	18.0 MB
02. What is a Distribution.vtt	6.0 KB
03. The Normal Distribution.mp4	13.7 MB
03. The Normal Distribution.vtt	5.3 KB
04. The Standard Normal Distribution.mp4	9.0 MB
04. The Standard Normal Distribution.vtt	4.1 KB
05. The Standard Normal Distribution Exercise.html	0.1 KB
06. Central Limit Theorem.mp4	24.3 MB
06. Central Limit Theorem.vtt	5.7 KB
07. Standard error.mp4	14.2 MB
07. Standard error.vtt	2.1 KB
08. Estimators and Estimates.mp4	29.0 MB
08. Estimators and Estimates.vtt	4.1 KB
/assets/
01. Course-notes-inferential-statistics.pdf	391.5 KB
02. 3.2.What-is-a-distribution-lesson.xlsx	19.9 KB
02. Course-notes-inferential-statistics.pdf	391.5 KB
04. 3.4.Standard-normal-distribution-lesson.xlsx	10.6 KB
05. 3.4.Standard-normal-distribution-exercise-solution.xlsx	24.6 KB
05. 3.4.Standard-normal-distribution-exercise.xlsx	12.3 KB
/18. Statistics - Inferential Statistics Confidence Intervals/
01. What are Confidence Intervals.mp4	30.0 MB
01. What are Confidence Intervals.vtt	3.3 KB
02. Confidence Intervals; Population Variance Known; Z-score.mp4	54.7 MB
02. Confidence Intervals; Population Variance Known; Z-score.vtt	9.8 KB
03. Confidence Intervals; Population Variance Known; Z-score; Exercise.html	0.1 KB
04. Confidence Interval Clarifications.mp4	19.9 MB
04. Confidence Interval Clarifications.vtt	5.7 KB
05. Student's T Distribution.mp4	14.3 MB
05. Student's T Distribution.vtt	4.7 KB
06. Confidence Intervals; Population Variance Unknown; T-score.mp4	14.4 MB
06. Confidence Intervals; Population Variance Unknown; T-score.vtt	5.5 KB
07. Confidence Intervals; Population Variance Unknown; T-score; Exercise.html	0.1 KB
08. Margin of Error.mp4	24.2 MB
08. Margin of Error.vtt	6.6 KB
09. Confidence intervals. Two means. Dependent samples.mp4	47.2 MB
09. Confidence intervals. Two means. Dependent samples.vtt	8.7 KB
10. Confidence intervals. Two means. Dependent samples Exercise.html	0.1 KB
11. Confidence intervals. Two means. Independent Samples (Part 1).mp4	12.6 MB
11. Confidence intervals. Two means. Independent Samples (Part 1).vtt	6.4 KB
12. Confidence intervals. Two means. Independent Samples (Part 1). Exercise.html	0.1 KB
13. Confidence intervals. Two means. Independent Samples (Part 2).mp4	15.3 MB
13. Confidence intervals. Two means. Independent Samples (Part 2).vtt	4.8 KB
14. Confidence intervals. Two means. Independent Samples (Part 2). Exercise.html	0.1 KB
15. Confidence intervals. Two means. Independent Samples (Part 3).mp4	7.2 MB
15. Confidence intervals. Two means. Independent Samples (Part 3).vtt	2.1 KB
/assets/
02. 3.9.Population-variance-known-z-score-lesson.xlsx	11.5 KB
02. 3.9.The-z-table.xlsx	26.2 KB
03. 3.9.Population-variance-known-z-score-exercise-solution.xlsx	11.4 KB
03. 3.9.Population-variance-known-z-score-exercise.xlsx	11.1 KB
03. 3.9.The-z-table.xlsx	26.2 KB
06. 3.11.Population-variance-unknown-t-score-lesson.xlsx	11.0 KB
06. 3.11.The-t-table.xlsx	16.2 KB
07. 3.11.Population-variance-unknown-t-score-exercise-solution.xlsx	11.4 KB
07. 3.11.Population-variance-unknown-t-score-exercise.xlsx	10.9 KB
07. 3.11.The-t-table.xlsx	16.2 KB
09. 3.13.Confidence-intervals.Two-means.Dependent-samples-lesson.xlsx	10.7 KB
10. 3.13.Confidence-intervals.Two-means.Dependent-samples-exercise-solution.xlsx	14.6 KB
10. 3.13.Confidence-intervals.Two-means.Dependent-samples-exercise.xlsx	14.1 KB
11. 3.14.Confidence-intervals.Two-means.Independent-samples-Part-1-lesson.xlsx	10.1 KB
12. 3.14.Confidence-intervals.Two-means.Independent-samples-Part-1-exercise-solution.xlsx	10.4 KB
12. 3.14.Confidence-intervals.Two-means.Independent-samples-Part-1-exercise.xlsx	10.1 KB
13. 3.15.Confidence-intervals.Two-means.Independent-samples-Part-2-lesson.xlsx	9.7 KB
14. 3.15.Confidence-intervals.Two-means.Independent-samples-Part-2-exercise-solution.xlsx	10.0 KB
14. 3.15.Confidence-intervals.Two-means.Independent-samples-Part-2-exercise.xlsx	9.4 KB
/19. Statistics - Practical Example Inferential Statistics/
01. Practical Example Inferential Statistics.mp4	72.4 MB
01. Practical Example Inferential Statistics.vtt	14.2 KB
02. Practical Example Inferential Statistics Exercise.html	0.1 KB
/assets/
01. 3.17.Practical-example.Confidence-intervals-lesson.xlsx	1.8 MB
02. 3.17.Practical-example.Confidence-intervals-exercise-solution.xlsx	1.9 MB
02. 3.17.Practical-example.Confidence-intervals-exercise.xlsx	1.8 MB
/20. Statistics - Hypothesis Testing/
01. Null vs Alternative Hypothesis.mp4	33.5 MB
01. Null vs Alternative Hypothesis.vtt	7.3 KB
02. Further Reading on Null and Alternative Hypothesis.html	2.3 KB
03. Rejection Region and Significance Level.mp4	40.6 MB
03. Rejection Region and Significance Level.vtt	8.8 KB
04. Type I Error and Type II Error.mp4	16.0 MB
04. Type I Error and Type II Error.vtt	5.6 KB
05. Test for the Mean. Population Variance Known.mp4	38.7 MB
05. Test for the Mean. Population Variance Known.vtt	8.3 KB
06. Test for the Mean. Population Variance Known Exercise.html	0.1 KB
07. p-value.mp4	35.4 MB
07. p-value.vtt	5.4 KB
08. Test for the Mean. Population Variance Unknown.mp4	20.7 MB
08. Test for the Mean. Population Variance Unknown.vtt	6.1 KB
09. Test for the Mean. Population Variance Unknown Exercise.html	0.1 KB
10. Test for the Mean. Dependent Samples.mp4	34.4 MB
10. Test for the Mean. Dependent Samples.vtt	6.9 KB
11. Test for the Mean. Dependent Samples Exercise.html	0.1 KB
12. Test for the mean. Independent Samples (Part 1).mp4	16.2 MB
12. Test for the mean. Independent Samples (Part 1).vtt	5.6 KB
13. Test for the mean. Independent Samples (Part 1). Exercise.html	0.1 KB
14. Test for the mean. Independent Samples (Part 2).mp4	25.6 MB
14. Test for the mean. Independent Samples (Part 2).vtt	5.5 KB
15. Test for the mean. Independent Samples (Part 2). Exercise.html	0.1 KB
/assets/
01. Course-notes-hypothesis-testing.pdf	672.2 KB
03. Course-notes-hypothesis-testing.pdf	672.2 KB
05. 4.4.Test-for-the-mean.Population-variance-known-lesson.xlsx	11.2 KB
06. 4.4.Test-for-the-mean.Population-variance-known-exercise-solution.xlsx	11.5 KB
06. 4.4.Test-for-the-mean.Population-variance-known-exercise.xlsx	11.3 KB
07. Online-p-value-calculator.pdf	1.2 MB
08. 4.6.Test-for-the-mean.Population-variance-unknown-lesson.xlsx	14.9 KB
09. 4.6.Test-for-the-mean.Population-variance-unknown-exercise-solution.xlsx	12.9 KB
09. 4.6.Test-for-the-mean.Population-variance-unknown-exercise.xlsx	11.6 KB
10. 4.7.Test-for-the-mean.Dependent-samples-lesson.xlsx	10.0 KB
11. 4.7.Test-for-the-mean.Dependent-samples-exercise-solution.xlsx	14.7 KB
11. 4.7.Test-for-the-mean.Dependent-samples-exercise.xlsx	13.1 KB
12. 4.8.Test-for-the-mean.Independent-samples-Part-1-lesson.xlsx	9.9 KB
13. 4.8.Test-for-the-mean.Independent-samples-Part-1-exercise-solution.xlsx	11.5 KB
13. 4.8.Test-for-the-mean.Independent-samples-Part-1-exercise.xlsx	11.0 KB
14. 4.9.Test-for-the-mean.Independent-samples-Part-2-lesson.xlsx	9.5 KB
15. 4.9.Test-for-the-mean.Independent-samples-Part-2-exercise-2-solution.xlsx	11.7 KB
15. 4.9.Test-for-the-mean.Independent-samples-Part-2-exercise-2.xlsx	10.8 KB
/21. Statistics - Practical Example Hypothesis Testing/
01. Practical Example Hypothesis Testing.mp4	48.1 MB
01. Practical Example Hypothesis Testing.vtt	8.8 KB
02. Practical Example Hypothesis Testing Exercise.html	0.1 KB
/assets/
01. 4.10.Hypothesis-testing-section-practical-example.xlsx	53.1 KB
02. 4.10.Hypothesis-testing-section-practical-example-exercise-solution.xlsx	45.3 KB
02. 4.10.Hypothesis-testing-section-practical-example-exercise.xlsx	44.7 KB
/22. Part 4 Introduction to Python/
01. Introduction to Programming.mp4	15.6 MB
01. Introduction to Programming.vtt	7.5 KB
02. Why Python.mp4	12.8 MB
02. Why Python.vtt	7.3 KB
03. Why Jupyter.mp4	8.4 MB
03. Why Jupyter.vtt	4.3 KB
04. Installing Python and Jupyter.mp4	19.7 MB
04. Installing Python and Jupyter.vtt	5.0 KB
05. Understanding Jupyter's Interface - the Notebook Dashboard.mp4	6.4 MB
05. Understanding Jupyter's Interface - the Notebook Dashboard.vtt	3.8 KB
06. Prerequisites for Coding in the Jupyter Notebooks.mp4	19.9 MB
06. Prerequisites for Coding in the Jupyter Notebooks.vtt	8.1 KB
/assets/
01. Introduction-to-Python-Course-Notes.pdf	2.3 MB
/23. Python - Variables and Data Types/
01. Variables.mp4	9.4 MB
01. Variables.vtt	4.9 KB
02. Numbers and Boolean Values in Python.mp4	6.9 MB
02. Numbers and Boolean Values in Python.vtt	3.8 KB
03. Python Strings.mp4	20.7 MB
03. Python Strings.vtt	7.8 KB
/assets/
01. Introduction-to-Python-Course-Notes.pdf	2.3 MB
01. Variables-Exercise-Py3.ipynb	2.3 KB
01. Variables-Lecture-Py3.ipynb	3.7 KB
01. Variables-Solution-Py3.ipynb	3.9 KB
02. Numbers-and-Boolean-Values-Exercise-Py3.ipynb	2.3 KB
02. Numbers-and-Boolean-Values-Lecture-Py3.ipynb	3.4 KB
02. Numbers-and-Boolean-Values-Solution-Py3.ipynb	3.3 KB
03. Strings-Exercise-Py3.ipynb	2.7 KB
03. Strings-Lecture-Py3.ipynb	7.7 KB
03. Strings-Solution-Py3.ipynb	5.6 KB
/24. Python - Basic Python Syntax/
01. Using Arithmetic Operators in Python.mp4	9.0 MB
01. Using Arithmetic Operators in Python.vtt	4.5 KB
02. The Double Equality Sign.mp4	2.8 MB
02. The Double Equality Sign.vtt	1.9 KB
03. How to Reassign Values.mp4	2.0 MB
03. How to Reassign Values.vtt	1.4 KB
04. Add Comments.mp4	2.5 MB
04. Add Comments.vtt	2.0 KB
05. Understanding Line Continuation.mp4	1.3 MB
05. Understanding Line Continuation.vtt	1.2 KB
06. Indexing Elements.mp4	2.5 MB
06. Indexing Elements.vtt	1.7 KB
07. Structuring with Indentation.mp4	2.9 MB
07. Structuring with Indentation.vtt	2.4 KB
/assets/
01. Arithmetic-Operators-Exercise-Py3.ipynb	2.7 KB
01. Arithmetic-Operators-Lecture-Py3.ipynb	3.6 KB
01. Arithmetic-Operators-Solution-Py3.ipynb	4.3 KB
02. The-Double-Equality-Sign-Exercise-Py3.ipynb	0.8 KB
02. The-Double-Equality-Sign-Lecture-Py3.ipynb	1.5 KB
02. The-Double-Equality-Sign-Solution-Py3.ipynb	1.2 KB
03. Reassign-Values-Exercise-Py3.ipynb	1.7 KB
03. Reassign-Values-Lecture-Py3.ipynb	3.2 KB
03. Reassign-Values-Solution-Py3.ipynb	2.2 KB
04. Add-Comments-Lecture-Py3.ipynb	1.1 KB
05. Line-Continuation-Exercise-Py3.ipynb	1.2 KB
05. Line-Continuation-Lecture-Py3.ipynb	0.8 KB
05. Line-Continuation-Solution-Py3.ipynb	1.5 KB
06. Indexing-Elements-Exercise-Py3.ipynb	1.4 KB
06. Indexing-Elements-Lecture-Py3.ipynb	1.3 KB
06. Indexing-Elements-Solution-Py3.ipynb	2.2 KB
07. Structure-Your-Code-with-Indentation-Exercise-Py3.ipynb	1.0 KB
07. Structure-Your-Code-with-Indentation-Lecture-Py3.ipynb	1.0 KB
07. Structure-Your-Code-with-Indentation-Solution-Py3.ipynb	1.5 KB
/25. Python - Other Python Operators/
01. Comparison Operators.mp4	4.4 MB
01. Comparison Operators.vtt	2.6 KB
02. Logical and Identity Operators.mp4	19.9 MB
02. Logical and Identity Operators.vtt	6.1 KB
/assets/
01. Comparison-Operators-Exercise-Py3.ipynb	1.6 KB
01. Comparison-Operators-Lecture-Py3.ipynb	2.6 KB
01. Comparison-Operators-Solution-Py3.ipynb	2.5 KB
02. Logical-and-Identity-Operators-Lecture-Py3.ipynb	6.0 KB
02. Logical-and-Identity-Operators-Solution-Py3.ipynb	3.5 KB
/26. Python - Conditional Statements/
01. The IF Statement.mp4	7.0 MB
01. The IF Statement.vtt	3.8 KB
02. The ELSE Statement.mp4	6.3 MB
02. The ELSE Statement.vtt	3.3 KB
03. The ELIF Statement.mp4	14.9 MB
03. The ELIF Statement.vtt	7.0 KB
04. A Note on Boolean Values.mp4	4.4 MB
04. A Note on Boolean Values.vtt	3.2 KB
/assets/
01. Introduction-to-the-If-Statement-Exercise-Py3.ipynb	1.6 KB
01. Introduction-to-the-If-Statement-Lecture-Py3.ipynb	1.2 KB
01. Introduction-to-the-If-Statement-Solution-Py3.ipynb	2.2 KB
02. Add-an-Else-Statement-Exercise-Py3.ipynb	1.0 KB
02. Add-an-Else-Statement-Lecture-Py3.ipynb	1.8 KB
02. Add-an-Else-Statement-Solution-Py3.ipynb	1.4 KB
03. Else-If-for-Brief-Elif-Exercise-Py3.ipynb	1.8 KB
03. Else-If-for-Brief-Elif-Lecture-Py3.ipynb	3.3 KB
03. Else-If-for-Brief-Elif-Solution-Py3.ipynb	2.5 KB
04. A-Note-on-Boolean-Values-Lecture-Py3.ipynb	0.8 KB
/27. Python - Python Functions/
01. Defining a Function in Python.mp4	3.4 MB
01. Defining a Function in Python.vtt	2.7 KB
02. How to Create a Function with a Parameter.mp4	10.5 MB
02. How to Create a Function with a Parameter.vtt	4.6 KB
03. Defining a Function in Python - Part II.mp4	6.8 MB
03. Defining a Function in Python - Part II.vtt	3.1 KB
04. How to Use a Function within a Function.mp4	3.4 MB
04. How to Use a Function within a Function.vtt	2.1 KB
05. Conditional Statements and Functions.mp4	6.3 MB
05. Conditional Statements and Functions.vtt	3.7 KB
06. Functions Containing a Few Arguments.mp4	2.9 MB
06. Functions Containing a Few Arguments.vtt	1.5 KB
07. Built-in Functions in Python.mp4	10.7 MB
07. Built-in Functions in Python.vtt	4.4 KB
/assets/
01. Defining-a-Function-in-Python-Lecture-Py3.ipynb	0.9 KB
02. Creating-a-Function-with-a-Parameter-Exercise-Py3.ipynb	1.2 KB
02. Creating-a-Function-with-a-Parameter-Lecture-Py3.ipynb	1.6 KB
02. Creating-a-Function-with-a-Parameter-Solution-Py3.ipynb	1.8 KB
03. Another-Way-to-Define-a-Function-Exercise-Py3.ipynb	1.3 KB
03. Another-Way-to-Define-a-Function-Lecture-Py3.ipynb	3.4 KB
03. Another-Way-to-Define-a-Function-Solution-Py3.ipynb	2.0 KB
04. 0.6.4-Using-a-Function-in-another-Function-Exercise-Py3.ipynb	1.1 KB
04. 0.6.4-Using-a-Function-in-another-Function-Lecture-Py3.ipynb	1.0 KB
04. 0.6.4-Using-a-Function-in-another-Function-Solution-Py3.ipynb	1.6 KB
05. Combining-Conditional-Statements-and-Functions-Exercise-Py3.ipynb	1.1 KB
05. Combining-Conditional-Statements-and-Functions-Lecture-Py3.ipynb	1.3 KB
05. Combining-Conditional-Statements-and-Functions-Solution-Py3.ipynb	1.7 KB
06. Creating-Functions-Containing-a-Few-Arguments-Lecture-Py3.ipynb	1.8 KB
07. Notable-Built-In-Functions-in-Python-Exercise-Py3.ipynb	3.7 KB
07. Notable-Built-In-Functions-in-Python-Lecture-Py3.ipynb	4.6 KB
07. Notable-Built-In-Functions-in-Python-Solution-Py3.ipynb	5.7 KB
/28. Python - Sequences/
01. Lists.mp4	24.2 MB
01. Lists.vtt	10.6 KB
02. Using Methods.mp4	31.8 MB
02. Using Methods.vtt	8.9 KB
03. List Slicing.mp4	20.1 MB
03. List Slicing.vtt	5.7 KB
04. Tuples.mp4	19.1 MB
04. Tuples.vtt	7.7 KB
05. Dictionaries.mp4	34.0 MB
05. Dictionaries.vtt	9.1 KB
/assets/
01. Lists-Exercise-Py3.ipynb	2.2 KB
01. Lists-Lecture-Py3.ipynb	2.8 KB
01. Lists-Solution-Py3.ipynb	3.3 KB
02. Help-Yourself-with-Methods-Exercise-Py3.ipynb	2.0 KB
02. Help-Yourself-with-Methods-Lecture-Py3.ipynb	4.5 KB
02. Help-Yourself-with-Methods-Solution-Py3.ipynb	2.9 KB
03. List-Slicing-Exercise-Py3.ipynb	2.9 KB
03. List-Slicing-Lecture-Py3.ipynb	5.1 KB
03. List-Slicing-Solution-Py3.ipynb	4.4 KB
04. Tuples-Exercise-Py3.ipynb	2.1 KB
04. Tuples-Lecture-Py3.ipynb	3.0 KB
04. Tuples-Solution-Py3.ipynb	4.7 KB
05. Dictionaries-Exercise-Py3.ipynb	3.0 KB
05. Dictionaries-Lecture-Py3.ipynb	4.5 KB
05. Dictionaries-Solution-Py3.ipynb	6.3 KB
/29. Python - Iterations/
01. For Loops.mp4	13.6 MB
01. For Loops.vtt	6.9 KB
02. While Loops and Incrementing.mp4	21.2 MB
02. While Loops and Incrementing.vtt	6.2 KB
03. Lists with the range() Function.mp4	16.8 MB
03. Lists with the range() Function.vtt	8.8 KB
04. Conditional Statements and Loops.mp4	18.2 MB
04. Conditional Statements and Loops.vtt	8.2 KB
05. Conditional Statements, Functions, and Loops.mp4	4.5 MB
05. Conditional Statements, Functions, and Loops.vtt	2.5 KB
06. How to Iterate over Dictionaries.mp4	19.3 MB
06. How to Iterate over Dictionaries.vtt	8.0 KB
/assets/
01. For-Loops-Exercise-Py3.ipynb	1.3 KB
01. For-Loops-Lecture-Py3.ipynb	1.3 KB
01. For-Loops-Solution-Py3.ipynb	1.8 KB
02. While-Loops-and-Incrementing-Exercise-Py3.ipynb	1.1 KB
02. While-Loops-and-Incrementing-Lecture-Py3.ipynb	1.1 KB
02. While-Loops-and-Incrementing-Solution-Py3.ipynb	1.8 KB
03. Create-Lists-with-the-range-Function-Exercise-Py3.ipynb	1.5 KB
03. Create-Lists-with-the-range-Function-Lecture-Py3.ipynb	1.4 KB
03. Create-Lists-with-the-range-Function-Solution-Py3.ipynb	2.3 KB
04. Use-Conditional-Statements-and-Loops-Together-Exercise-Py3.ipynb	2.1 KB
04. Use-Conditional-Statements-and-Loops-Together-Lecture-Py3.ipynb	2.0 KB
04. Use-Conditional-Statements-and-Loops-Together-Solution-Py3.ipynb	3.0 KB
05. All-In-Exercise-Py3.ipynb	1.3 KB
05. All-In-Lecture-Py3.ipynb	1.7 KB
05. All-In-Solution-Py3.ipynb	1.9 KB
06. Iterating-over-Dictionaries-Exercise-Py3.ipynb	2.2 KB
06. Iterating-over-Dictionaries-Lecture-Py3.ipynb	1.1 KB
06. Iterating-over-Dictionaries-Solution-Py3.ipynb	2.9 KB
/30. Python - Advanced Python Tools/
01. Object Oriented Programming.mp4	9.1 MB
01. Object Oriented Programming.vtt	7.0 KB
02. Modules and Packages.mp4	2.2 MB
02. Modules and Packages.vtt	1.5 KB
03. What is the Standard Library.mp4	5.3 MB
03. What is the Standard Library.vtt	4.0 KB
04. Importing Modules in Python.mp4	10.4 MB
04. Importing Modules in Python.vtt	5.0 KB
/31. Part 5 Advanced Statistical Methods in Python/
01. Introduction to Regression Analysis.mp4	3.8 MB
01. Introduction to Regression Analysis.vtt	2.4 KB
/assets/
01. Course-notes-regression-analysis.pdf	319.7 KB
/32. Advanced Statistical Methods - Linear Regression with StatsModels/
01. The Linear Regression Model.mp4	14.1 MB
01. The Linear Regression Model.vtt	8.3 KB
02. Correlation vs Regression.mp4	4.0 MB
02. Correlation vs Regression.vtt	2.2 KB
03. Geometrical Representation of the Linear Regression Model.mp4	2.4 MB
03. Geometrical Representation of the Linear Regression Model.vtt	1.8 KB
04. Python Packages Installation.mp4	24.8 MB
04. Python Packages Installation.vtt	5.7 KB
05. First Regression in Python.mp4	31.0 MB
05. First Regression in Python.vtt	8.4 KB
06. First Regression in Python Exercise.html	1.4 KB
07. Using Seaborn for Graphs.mp4	7.7 MB
07. Using Seaborn for Graphs.vtt	1.6 KB
08. How to Interpret the Regression Table.mp4	30.1 MB
08. How to Interpret the Regression Table.vtt	6.5 KB
09. Decomposition of Variability.mp4	9.2 MB
09. Decomposition of Variability.vtt	4.6 KB
10. What is the OLS.mp4	23.6 MB
10. What is the OLS.vtt	3.9 KB
11. R-Squared.mp4	11.7 MB
11. R-Squared.vtt	7.0 KB
/assets/
01. Course-notes-regression-analysis.pdf	319.7 KB
05. 1.01.Simple-linear-regression.csv	0.9 KB
05. Simple-linear-regression-with-comments.ipynb	4.2 KB
05. Simple-linear-regression.ipynb	3.9 KB
06. real-estate-price-size.csv	1.9 KB
06. Simple-Linear-Regression-Exercise-Solution.ipynb	3.7 KB
06. Simple-Linear-Regression-Exercise.ipynb	2.8 KB
/33. Advanced Statistical Methods - Multiple Linear Regression with StatsModels/
01. Multiple Linear Regression.mp4	6.0 MB
01. Multiple Linear Regression.vtt	3.5 KB
02. Adjusted R-Squared.mp4	35.9 MB
02. Adjusted R-Squared.vtt	7.7 KB
03. Multiple Linear Regression Exercise.html	0.1 KB
04. Test for Significance of the Model (F-Test).mp4	7.5 MB
04. Test for Significance of the Model (F-Test).vtt	2.5 KB
05. OLS Assumptions.mp4	5.5 MB
05. OLS Assumptions.vtt	3.1 KB
06. A1 Linearity.mp4	3.7 MB
06. A1 Linearity.vtt	2.5 KB
07. A2 No Endogeneity.mp4	9.7 MB
07. A2 No Endogeneity.vtt	5.7 KB
08. A3 Normality and Homoscedasticity.mp4	28.7 MB
08. A3 Normality and Homoscedasticity.vtt	7.2 KB
09. A4 No Autocorrelation.mp4	8.3 MB
09. A4 No Autocorrelation.vtt	5.1 KB
10. A5 No Multicollinearity.mp4	8.0 MB
10. A5 No Multicollinearity.vtt	4.7 KB
11. Dealing with Categorical Data - Dummy Variables.mp4	23.7 MB
11. Dealing with Categorical Data - Dummy Variables.vtt	9.8 KB
12. Dealing with Categorical Data - Dummy Variables.html	0.1 KB
13. Making Predictions with the Linear Regression.mp4	17.1 MB
13. Making Predictions with the Linear Regression.vtt	4.5 KB
/assets/
02. 1.02.Multiple-linear-regression.csv	1.1 KB
02. Multiple-linear-regression-and-Adjusted-R-squared-with-comments.ipynb	2.9 KB
02. Multiple-linear-regression-and-Adjusted-R-squared.ipynb	2.2 KB
03. Multiple-Linear-Regression-Exercise-Solution.ipynb	13.7 KB
03. Multiple-Linear-Regression-Exercise.ipynb	2.5 KB
03. real-estate-price-size-year.csv	2.4 KB
11. 1.03.Dummies.csv	1.2 KB
11. Dummy-variables-with-comments.ipynb	7.3 KB
11. Dummy-Variables.ipynb	4.7 KB
12. Multiple-Linear-Regression-with-Dummies-Exercise-Solution.ipynb	18.4 KB
12. Multiple-Linear-Regression-with-Dummies-Exercise.ipynb	3.1 KB
12. real-estate-price-size-year-view.csv	3.5 KB
13. Making-predictions-with-comments.ipynb	9.6 KB
13. Making-predictions.ipynb	5.9 KB
/34. Advanced Statistical Methods - Linear Regression with sklearn/
01. What is sklearn and How is it Different from Other Packages.mp4	8.9 MB
01. What is sklearn and How is it Different from Other Packages.vtt	3.7 KB
02. How are we Going to Approach this Section.mp4	5.6 MB
02. How are we Going to Approach this Section.vtt	3.1 KB
03. Simple Linear Regression with sklearn.mp4	28.8 MB
03. Simple Linear Regression with sklearn.vtt	7.8 KB
04. Simple Linear Regression with sklearn - A StatsModels-like Summary Table.mp4	23.4 MB
04. Simple Linear Regression with sklearn - A StatsModels-like Summary Table.vtt	6.9 KB
05. A Note on Normalization.html	0.7 KB
06. Simple Linear Regression with sklearn - Exercise.html	0.1 KB
07. Multiple Linear Regression with sklearn.mp4	8.7 MB
07. Multiple Linear Regression with sklearn.vtt	4.4 KB
08. Calculating the Adjusted R-Squared in sklearn.mp4	17.7 MB
08. Calculating the Adjusted R-Squared in sklearn.vtt	6.8 KB
09. Calculating the Adjusted R-Squared in sklearn - Exercise.html	0.1 KB
10. Feature Selection (F-regression).mp4	21.5 MB
10. Feature Selection (F-regression).vtt	7.1 KB
11. A Note on Calculation of P-values with sklearn.html	0.4 KB
12. Creating a Summary Table with P-values.mp4	6.8 MB
12. Creating a Summary Table with P-values.vtt	3.1 KB
13. Multiple Linear Regression - Exercise.html	0.1 KB
14. Feature Scaling (Standardization).mp4	21.4 MB
14. Feature Scaling (Standardization).vtt	9.0 KB
15. Feature Selection through Standardization of Weights.mp4	25.7 MB
15. Feature Selection through Standardization of Weights.vtt	7.8 KB
16. Predicting with the Standardized Coefficients.mp4	21.4 MB
16. Predicting with the Standardized Coefficients.vtt	5.7 KB
17. Feature Scaling (Standardization) - Exercise.html	0.1 KB
18. Underfitting and Overfitting.mp4	6.1 MB
18. Underfitting and Overfitting.vtt	3.8 KB
19. Train - Test Split Explained.mp4	37.3 MB
19. Train - Test Split Explained.vtt	9.9 KB
/assets/
03. 1.01.Simple-linear-regression.csv	0.9 KB
03. sklearn-Simple-Linear-Regression-with-comments.ipynb	6.2 KB
03. sklearn-Simple-Linear-Regression.ipynb	5.0 KB
04. 1.01.Simple-linear-regression.csv	0.9 KB
04. sklearn-Simple-Linear-Regression-with-comments.ipynb	29.0 KB
04. sklearn-Simple-Linear-Regression.ipynb	26.7 KB
06. real-estate-price-size.csv	1.9 KB
06. Simple-Linear-Regression-with-sklearn-Exercise-Solution.ipynb	27.2 KB
06. Simple-Linear-Regression-with-sklearn-Exercise.ipynb	4.2 KB
07. 1.02.Multiple-linear-regression.csv	1.1 KB
07. sklearn-Multiple-Linear-Regression-with-comments.ipynb	8.9 KB
07. sklearn-Multiple-Linear-Regression.ipynb	8.0 KB
08. 1.02.Multiple-linear-regression.csv	1.1 KB
08. sklearn-Multiple-Linear-Regression-and-Adjusted-R-squared-with-comments.ipynb	10.7 KB
08. sklearn-Multiple-Linear-Regression-and-Adjusted-R-squared.ipynb	9.3 KB
09. 1.02.Multiple-linear-regression.csv	1.1 KB
09. sklearn-Multiple-Linear-Regression-and-Adjusted-R-squared-Exercise-Solution.ipynb	10.6 KB
09. sklearn-Multiple-Linear-Regression-and-Adjusted-R-squared-Exercise.ipynb	10.1 KB
10. 1.02.Multiple-linear-regression.csv	1.1 KB
10. sklearn-Feature-Selection-with-F-regression-with-comments.ipynb	13.3 KB
10. sklearn-Feature-Selection-with-F-regression.ipynb	10.7 KB
11. 1.02.Multiple-linear-regression.csv	1.1 KB
11. sklearn-How-to-properly-include-p-values.ipynb	13.0 KB
12. 1.02.Multiple-linear-regression.csv	1.1 KB
12. sklearn-Multiple-Linear-Regression-Summary-Table-with-comments.ipynb	17.0 KB
12. sklearn-Multiple-Linear-Regression-Summary-Table.ipynb	14.0 KB
13. real-estate-price-size-year.csv	2.4 KB
13. sklearn-Multiple-Linear-Regression-Exercise-Solution.ipynb	15.8 KB
13. sklearn-Multiple-Linear-Regression-Exercise.ipynb	5.8 KB
14. 1.02.Multiple-linear-regression.csv	1.1 KB
14. SKLEAR-1.IPY	13.2 KB
14. sklearn-Feature-Selection-through-Feature-Scaling-Standardization-Part-1.ipynb	12.0 KB
15. 1.02.Multiple-linear-regression.csv	1.1 KB
15. SKLEAR-1.IPY	17.2 KB
15. sklearn-Feature-Selection-through-Feature-Scaling-Standardization-Part-2.ipynb	15.3 KB
16. 1.02.Multiple-linear-regression.csv	1.1 KB
16. sklearn-Making-Predictions-with-the-Standardized-Coefficients-with-comments.ipynb	22.6 KB
16. sklearn-Making-Predictions-with-the-Standardized-Coefficients.ipynb	30.5 KB
17. real-estate-price-size-year.csv	2.4 KB
17. sklearn-Feature-Scaling-Exercise-Solution.ipynb	16.7 KB
17. sklearn-Feature-Scaling-Exercise.ipynb	6.2 KB
19. sklearn-Train-Test-Split-with-comments.ipynb	9.3 KB
19. sklearn-Train-Test-Split.ipynb	7.4 KB
/35. Advanced Statistical Methods - Practical Example Linear Regression/
01. Practical Example Linear Regression (Part 1).mp4	88.9 MB
01. Practical Example Linear Regression (Part 1).vtt	15.2 KB
02. Practical Example Linear Regression (Part 2).mp4	33.4 MB
02. Practical Example Linear Regression (Part 2).vtt	8.5 KB
03. A Note on Multicollinearity.html	0.8 KB
04. Practical Example Linear Regression (Part 3).mp4	17.5 MB
04. Practical Example Linear Regression (Part 3).vtt	4.6 KB
05. Dummies and Variance Inflation Factor - Exercise.html	0.1 KB
06. Practical Example Linear Regression (Part 4).mp4	41.3 MB
06. Practical Example Linear Regression (Part 4).vtt	12.1 KB
07. Dummy Variables - Exercise.html	0.7 KB
08. Practical Example Linear Regression (Part 5).mp4	52.9 MB
08. Practical Example Linear Regression (Part 5).vtt	11.3 KB
09. Linear Regression - Exercise.html	0.5 KB
/assets/
01. 1.04.Real-life-example.csv	225.1 KB
01. sklearn-Linear-Regression-Practical-Example-Part-1-with-comments.ipynb	175.5 KB
01. sklearn-Linear-Regression-Practical-Example-Part-1.ipynb	170.9 KB
02. 1.04.Real-life-example.csv	225.1 KB
02. sklearn-Linear-Regression-Practical-Example-Part-2-with-comments.ipynb	343.7 KB
02. sklearn-Linear-Regression-Practical-Example-Part-2.ipynb	336.6 KB
04. sklearn-Linear-Regression-Practical-Example-Part-3-with-comments.ipynb	359.9 KB
04. sklearn-Linear-Regression-Practical-Example-Part-3.ipynb	351.8 KB
05. 1.04.Real-life-example.csv	225.1 KB
05. sklearn-Dummies-and-VIF-Exercise-Solution.ipynb	379.1 KB
05. sklearn-Dummies-and-VIF-Exercise.ipynb	352.9 KB
06. 1.04.Real-life-example.csv	225.1 KB
06. sklearn-Linear-Regression-Practical-Example-Part-4-with-comments.ipynb	417.4 KB
06. sklearn-Linear-Regression-Practical-Example-Part-4.ipynb	406.8 KB
08. 1.04.Real-life-example.csv	225.1 KB
08. sklearn-Linear-Regression-Practical-Example-Part-5-with-comments.ipynb	728.1 KB
08. sklearn-Linear-Regression-Practical-Example-Part-5.ipynb	715.1 KB
/36. Advanced Statistical Methods - Logistic Regression/
01. Introduction to Logistic Regression.mp4	6.2 MB
01. Introduction to Logistic Regression.vtt	1.9 KB
02. A Simple Example in Python.mp4	22.9 MB
02. A Simple Example in Python.vtt	6.0 KB
03. Logistic vs Logit Function.mp4	24.9 MB
03. Logistic vs Logit Function.vtt	5.2 KB
04. Building a Logistic Regression.mp4	9.0 MB
04. Building a Logistic Regression.vtt	3.6 KB
05. Building a Logistic Regression - Exercise.html	0.1 KB
06. An Invaluable Coding Tip.mp4	19.7 MB
06. An Invaluable Coding Tip.vtt	3.2 KB
07. Understanding Logistic Regression Tables.mp4	15.3 MB
07. Understanding Logistic Regression Tables.vtt	5.7 KB
08. Understanding Logistic Regression Tables - Exercise.html	0.1 KB
09. What do the Odds Actually Mean.mp4	11.9 MB
09. What do the Odds Actually Mean.vtt	4.5 KB
10. Binary Predictors in a Logistic Regression.mp4	26.1 MB
10. Binary Predictors in a Logistic Regression.vtt	5.4 KB
11. Binary Predictors in a Logistic Regression - Exercise.html	0.1 KB
12. Calculating the Accuracy of the Model.mp4	21.2 MB
12. Calculating the Accuracy of the Model.vtt	4.4 KB
13. Calculating the Accuracy of the Model.html	0.1 KB
14. Underfitting and Overfitting.mp4	7.8 MB
14. Underfitting and Overfitting.vtt	5.3 KB
15. Testing the Model.mp4	22.6 MB
15. Testing the Model.vtt	6.7 KB
16. Testing the Model - Exercise.html	0.1 KB
/assets/
01. Course-Notes-Logistic-Regression.pdf	343.2 KB
02. 2.01.Admittance.csv	1.6 KB
02. Admittance-with-comments.ipynb	5.4 KB
02. Admittance.ipynb	3.6 KB
02. Course-Notes-Logistic-Regression.pdf	343.2 KB
04. Admittance-regression-summary-error.ipynb	2.5 KB
04. Admittance-regression-tables-fixed-error.ipynb	4.2 KB
04. Admittance-regression.ipynb	2.1 KB
05. Building-a-Logistic-Regression-Exercise.ipynb	3.0 KB
05. Building-a-Logistic-Regression-Solution.ipynb	4.6 KB
05. Example-bank-data.csv	6.4 KB
08. Bank-data.csv	20.0 KB
08. Understanding-Logistic-Regression-Tables-Exercise.ipynb	3.2 KB
08. Understanding-Logistic-Regression-Tables-Solution.ipynb	4.9 KB
10. 2.02.Binary-predictors.csv	2.6 KB
10. Binary-predictors.ipynb	2.5 KB
11. Bank-data.csv	20.0 KB
11. Binary-Predictors-in-a-Logistic-Regression-Exercise.ipynb	2.6 KB
11. Binary-Predictors-in-a-Logistic-Regression-Solution.ipynb	4.6 KB
12. Accuracy-with-comments.ipynb	12.0 KB
12. Accuracy.ipynb	3.7 KB
13. Bank-data.csv	20.0 KB
13. Calculating-the-Accuracy-of-the-Model-Exercise.ipynb	5.5 KB
13. Calculating-the-Accuracy-of-the-Model-Solution.ipynb	83.2 KB
15. 2.03.Test-dataset.csv	0.3 KB
15. Testing-the-model-with-comments.ipynb	7.7 KB
15. Testing-the-model.ipynb	5.9 KB
16. Bank-data-testing.csv	8.5 KB
16. Bank-data.csv	20.0 KB
16. Testing-the-Model-Exercise.ipynb	7.0 KB
16. Testing-the-Model-Solution.ipynb	113.8 KB
/37. Advanced Statistical Methods - Cluster Analysis/
01. Introduction to Cluster Analysis.mp4	15.2 MB
01. Introduction to Cluster Analysis.vtt	5.1 KB
02. Some Examples of Clusters.mp4	37.6 MB
02. Some Examples of Clusters.vtt	6.4 KB
03. Difference between Classification and Clustering.mp4	10.1 MB
03. Difference between Classification and Clustering.vtt	3.7 KB
04. Math Prerequisites.mp4	5.5 MB
04. Math Prerequisites.vtt	4.5 KB
/assets/
01. Course-Notes-Cluster-Analysis.pdf	213.7 KB
02. Course-Notes-Cluster-Analysis.pdf	213.7 KB
/38. Advanced Statistical Methods - K-Means Clustering/
01. K-Means Clustering.mp4	11.3 MB
01. K-Means Clustering.vtt	6.8 KB
02. A Simple Example of Clustering.mp4	35.8 MB
02. A Simple Example of Clustering.vtt	10.0 KB
03. A Simple Example of Clustering - Exercise.html	0.1 KB
04. Clustering Categorical Data.mp4	10.9 MB
04. Clustering Categorical Data.vtt	3.4 KB
05. Clustering Categorical Data - Exercise.html	0.1 KB
06. How to Choose the Number of Clusters.mp4	28.2 MB
06. How to Choose the Number of Clusters.vtt	7.7 KB
07. How to Choose the Number of Clusters - Exercise.html	0.1 KB
08. Pros and Cons of K-Means Clustering.mp4	11.7 MB
08. Pros and Cons of K-Means Clustering.vtt	4.7 KB
09. To Standardize or not to Standardize.mp4	11.4 MB
09. To Standardize or not to Standardize.vtt	6.4 KB
10. Relationship between Clustering and Regression.mp4	3.7 MB
10. Relationship between Clustering and Regression.vtt	2.3 KB
11. Market Segmentation with Cluster Analysis (Part 1).mp4	29.4 MB
11. Market Segmentation with Cluster Analysis (Part 1).vtt	7.7 KB
12. Market Segmentation with Cluster Analysis (Part 2).mp4	35.7 MB
12. Market Segmentation with Cluster Analysis (Part 2).vtt	9.4 KB
13. How is Clustering Useful.mp4	39.3 MB
13. How is Clustering Useful.vtt	6.9 KB
14. EXERCISE Species Segmentation with Cluster Analysis (Part 1).html	0.1 KB
15. EXERCISE Species Segmentation with Cluster Analysis (Part 2).html	0.1 KB
/assets/
02. 3.01.Country-clusters.csv	0.2 KB
02. Country-clusters-with-comments.ipynb	5.9 KB
02. Country-clusters.ipynb	3.4 KB
03. A-Simple-Example-of-Clustering-Exercise.ipynb	3.7 KB
03. A-Simple-Example-of-Clustering-Solution.ipynb	4.8 KB
03. Countries-exercise.csv	8.5 KB
04. Categorical-data-with-comments.ipynb	5.8 KB
04. Categorical-data.ipynb	3.4 KB
05. Categorical.csv	10.6 KB
05. Clustering-Categorical-Data-Exercise.ipynb	3.9 KB
05. Clustering-Categorical-Data-Solution.ipynb	5.0 KB
06. Selecting-the-number-of-clusters-with-comments.ipynb	7.7 KB
06. Selecting-the-number-of-clusters.ipynb	4.6 KB
07. Countries-exercise.csv	8.5 KB
07. How-to-Choose-the-Number-of-Clusters-Exercise.ipynb	5.7 KB
07. How-to-Choose-the-Number-of-Clusters-Solution.ipynb	8.7 KB
11. 3.12.Example.csv	0.3 KB
11. Market-segmentation-example-with-comments.ipynb	6.0 KB
11. Market-segmentation-example.ipynb	3.9 KB
12. Market-segmentation-example-Part2-with-comments.ipynb	7.0 KB
12. Market-segmentation-example-Part2.ipynb	4.8 KB
14. iris-dataset.csv	2.5 KB
14. Species-Segmentation-with-Cluster-Analysis-Part-1-Exercise.ipynb	4.6 KB
14. Species-Segmentation-with-Cluster-Analysis-Part-1-Solution.ipynb	7.5 KB
15. iris-dataset.csv	2.5 KB
15. iris-with-answers.csv	3.7 KB
15. Species-Segmentation-with-Cluster-Analysis-Part-2-Exercise.ipynb	11.0 KB
15. Species-Segmentation-with-Cluster-Analysis-Part-2-Solution.ipynb	15.7 KB
/39. Advanced Statistical Methods - Other Types of Clustering/
01. Types of Clustering.mp4	9.4 MB
01. Types of Clustering.vtt	5.2 KB
02. Dendrogram.mp4	19.2 MB
02. Dendrogram.vtt	7.8 KB
03. Heatmaps.mp4	19.4 MB
03. Heatmaps.vtt	6.3 KB
/assets/
03. Country-clusters-standardized.csv	0.2 KB
03. Heatmaps-with-comments.ipynb	18.1 KB
03. Heatmaps.ipynb	1.9 KB
/40. ChatGPT for Data Science/
01. Traditional data science methods and the role of ChatGPT.mp4	27.4 MB
01. Traditional data science methods and the role of ChatGPT.vtt	7.4 KB
02. How to install ChatGPT.mp4	5.5 MB
02. How to install ChatGPT.vtt	2.1 KB
03. How ChatGPT can boost your productivity.mp4	5.6 MB
03. How ChatGPT can boost your productivity.vtt	2.5 KB
04. Data Preprocessing with ChatGPT.mp4	30.1 MB
04. Data Preprocessing with ChatGPT.vtt	6.6 KB
05. First attempt at machine learning with ChatGPT.mp4	38.5 MB
05. First attempt at machine learning with ChatGPT.vtt	6.5 KB
06. Analyzing a client database with ChatGPT in Python.mp4	22.7 MB
06. Analyzing a client database with ChatGPT in Python.vtt	5.3 KB
07. Analyzing a client database with ChatGPT in Python – analyzing top products.mp4	15.9 MB
07. Analyzing a client database with ChatGPT in Python – analyzing top products.vtt	5.3 KB
08. Analyzing a client database with ChatGPT in Python – analyzing top clients, RFM.mp4	28.5 MB
08. Analyzing a client database with ChatGPT in Python – analyzing top clients, RFM.vtt	6.0 KB
09. Exploratory data analysis (EDA) with ChatGPT - histogram and scatter plot.mp4	22.6 MB
09. Exploratory data analysis (EDA) with ChatGPT - histogram and scatter plot.vtt	7.6 KB
10. Exploratory data analysis (EDA) with ChatGPT - correlation matrix, outlier detec.mp4	35.3 MB
10. Exploratory data analysis (EDA) with ChatGPT - correlation matrix, outlier detec.vtt	7.7 KB
11. Assignment 1.html	1.7 KB
12. Hypothesis testing with ChatGPT.mp4	15.1 MB
12. Hypothesis testing with ChatGPT.vtt	5.8 KB
13. Marvels comic book database Intro to Regular Expressions (RegEx).mp4	15.7 MB
13. Marvels comic book database Intro to Regular Expressions (RegEx).vtt	2.8 KB
14. Decoding comic book data Python Regular Expressions and ChatGPT.mp4	34.7 MB
14. Decoding comic book data Python Regular Expressions and ChatGPT.vtt	6.6 KB
15. Assignment 2.html	1.6 KB
16. Algorithm recommendation Movie Database Analysis with ChatGPT.mp4	18.1 MB
16. Algorithm recommendation Movie Database Analysis with ChatGPT.vtt	4.5 KB
17. Algorithm recommendation recommendation engine for movies with ChatGPT.mp4	18.7 MB
17. Algorithm recommendation recommendation engine for movies with ChatGPT.vtt	6.5 KB
18. Ethical principles in data and AI utilization.mp4	15.4 MB
18. Ethical principles in data and AI utilization.vtt	4.5 KB
19. Using ChatGPT for ethical considerations.mp4	35.2 MB
19. Using ChatGPT for ethical considerations.vtt	7.7 KB
/assets/
04. Data-Preprocessing-Medical-Data.ipynb	7.7 KB
04. patients.csv	3.0 KB
05. diagnosis-mapping.csv	0.1 KB
05. Medical-Data-ML-Attempt.ipynb	4.5 KB
05. patients-preprocessed.csv	3.4 KB
06. customers.csv	1.6 KB
06. orders.csv	38.6 KB
06. products.csv	1.8 KB
06. ratings.csv	3.5 KB
08. Furniture-store-data-analysis.ipynb	53.6 KB
10. Properties-analysis.ipynb	293.4 KB
10. properties.csv	2.7 KB
12. Students-Hypothesis-Testing.ipynb	5.7 KB
12. students.csv	2.1 KB
14. Marvel-Comics-Reg-Ex.ipynb	30.2 KB
16. ratings-small.csv	2.4 MB
17. Movies-Data-Base-Recommendation-Engine.ipynb	20.9 KB
19. friendships.csv	6.1 KB
19. interactions.csv	75.0 KB
19. posts.csv	31.5 KB
19. users.csv	3.6 KB
/.../13. Marvel-Comics/
Marvel_Comics.csv	13.6 MB
/.../16. movies-metadata/
movies_metadata.csv	34.4 MB
/41. Case Study Train a Naive Bayes Classifier with ChatGPT for Sentiment Analysis/
01. Intro to the Case Study.mp4	10.9 MB
01. Intro to the Case Study.vtt	3.8 KB
02. The Naive Bayes Algorithm.mp4	44.1 MB
02. The Naive Bayes Algorithm.vtt	6.2 KB
03. Tokenization and Vectorization.mp4	16.6 MB
03. Tokenization and Vectorization.vtt	8.1 KB
04. Imbalanced Data Sets.mp4	6.9 MB
04. Imbalanced Data Sets.vtt	3.3 KB
05. Overcome Imbalanced Data in Machine Learning.mp4	15.3 MB
05. Overcome Imbalanced Data in Machine Learning.vtt	5.2 KB
06. Loading the Dataset and Preprocessing.mp4	15.5 MB
06. Loading the Dataset and Preprocessing.vtt	3.8 KB
07. Optimizing User Reviews Data Preprocessing & EDA.mp4	19.6 MB
07. Optimizing User Reviews Data Preprocessing & EDA.vtt	6.1 KB
08. Reg Ex for Analyzing Text Review Data.mp4	17.0 MB
08. Reg Ex for Analyzing Text Review Data.vtt	5.2 KB
09. Understanding Differences between Multinomial and Bernouilli Naive Bayes.mp4	14.5 MB
09. Understanding Differences between Multinomial and Bernouilli Naive Bayes.vtt	5.5 KB
10. Machine Learning with Naïve Bayes (First Attempt).mp4	29.5 MB
10. Machine Learning with Naïve Bayes (First Attempt).vtt	8.6 KB
11. Machine Learning with Naïve Bayes – converting the problem to a binary one.mp4	19.8 MB
11. Machine Learning with Naïve Bayes – converting the problem to a binary one.vtt	6.9 KB
12. Testing the Model on New Data.mp4	21.8 MB
12. Testing the Model on New Data.vtt	7.1 KB
/assets/
12. 365-User-Reviews-Naive-Bayes-Sentiment-Analysis.ipynb	1.8 MB
12. user-courses-review-test-set.csv	20.1 KB
/42. Part 6 Mathematics/
01. What is a Matrix.mp4	12.5 MB
01. What is a Matrix.vtt	4.7 KB
02. Scalars and Vectors.mp4	9.0 MB
02. Scalars and Vectors.vtt	4.1 KB
03. Linear Algebra and Geometry.mp4	14.4 MB
03. Linear Algebra and Geometry.vtt	4.2 KB
04. Arrays in Python - A Convenient Way To Represent Matrices.mp4	19.9 MB
04. Arrays in Python - A Convenient Way To Represent Matrices.vtt	6.4 KB
05. What is a Tensor.mp4	16.3 MB
05. What is a Tensor.vtt	3.9 KB
06. Addition and Subtraction of Matrices.mp4	23.2 MB
06. Addition and Subtraction of Matrices.vtt	4.3 KB
07. Errors when Adding Matrices.mp4	6.1 MB
07. Errors when Adding Matrices.vtt	2.8 KB
08. Transpose of a Matrix.mp4	14.9 MB
08. Transpose of a Matrix.vtt	5.7 KB
09. Dot Product.mp4	13.5 MB
09. Dot Product.vtt	4.4 KB
10. Dot Product of Matrices.mp4	36.0 MB
10. Dot Product of Matrices.vtt	9.3 KB
11. Why is Linear Algebra Useful.mp4	92.8 MB
11. Why is Linear Algebra Useful.vtt	11.8 KB
/assets/
04. Scalars-Vectors-and-Matrices.ipynb	4.7 KB
05. Tensors.ipynb	2.1 KB
06. Adding-and-subtracting-matrices.ipynb	3.3 KB
07. Errors-when-adding-scalars-vectors-and-matrices-in-Python.ipynb	3.2 KB
08. Tranpose-of-a-matrix.ipynb	3.0 KB
09. Dot-product.ipynb	2.2 KB
10. Dot-product-Part-2.ipynb	3.7 KB
/43. Part 7 Deep Learning/
01. What to Expect from this Part.mp4	12.3 MB
01. What to Expect from this Part.vtt	4.9 KB
/44. Deep Learning - Introduction to Neural Networks/
01. Introduction to Neural Networks.mp4	11.0 MB
01. Introduction to Neural Networks.vtt	6.4 KB
02. Training the Model.mp4	8.1 MB
02. Training the Model.vtt	4.9 KB
03. Types of Machine Learning.mp4	13.7 MB
03. Types of Machine Learning.vtt	5.6 KB
04. The Linear Model (Linear Algebraic Version).mp4	8.4 MB
04. The Linear Model (Linear Algebraic Version).vtt	3.8 KB
05. The Linear Model with Multiple Inputs.mp4	8.3 MB
05. The Linear Model with Multiple Inputs.vtt	2.9 KB
06. The Linear model with Multiple Inputs and Multiple Outputs.mp4	17.4 MB
06. The Linear model with Multiple Inputs and Multiple Outputs.vtt	5.0 KB
07. Graphical Representation of Simple Neural Networks.mp4	8.2 MB
07. Graphical Representation of Simple Neural Networks.vtt	2.8 KB
08. What is the Objective Function.mp4	6.5 MB
08. What is the Objective Function.vtt	2.3 KB
09. Common Objective Functions L2-norm Loss.mp4	5.7 MB
09. Common Objective Functions L2-norm Loss.vtt	3.0 KB
10. Common Objective Functions Cross-Entropy Loss.mp4	10.3 MB
10. Common Objective Functions Cross-Entropy Loss.vtt	5.5 KB
11. Optimization Algorithm 1-Parameter Gradient Descent.mp4	24.7 MB
11. Optimization Algorithm 1-Parameter Gradient Descent.vtt	9.0 KB
12. Optimization Algorithm n-Parameter Gradient Descent.mp4	17.7 MB
12. Optimization Algorithm n-Parameter Gradient Descent.vtt	8.0 KB
/assets/
01. Course-Notes-Section-2.pdf	592.0 KB
02. Course-Notes-Section-2.pdf	592.0 KB
11. GD-function-example.xlsx	43.4 KB
/45. Deep Learning - How to Build a Neural Network from Scratch with NumPy/
01. Basic NN Example (Part 1).mp4	9.8 MB
01. Basic NN Example (Part 1).vtt	4.6 KB
02. Basic NN Example (Part 2).mp4	16.0 MB
02. Basic NN Example (Part 2).vtt	6.8 KB
03. Basic NN Example (Part 3).mp4	16.4 MB
03. Basic NN Example (Part 3).vtt	4.5 KB
04. Basic NN Example (Part 4).mp4	41.9 MB
04. Basic NN Example (Part 4).vtt	11.2 KB
05. Basic NN Example Exercises.html	1.7 KB
/assets/
01. Minimal-example-Part-1.ipynb	1.2 KB
01. Shortcuts-for-Jupyter.pdf	634.0 KB
02. Minimal-example-Part-2.ipynb	3.7 KB
03. Minimal-example-Part-3.ipynb	7.0 KB
04. Minimal-example-Part-4-Complete.ipynb	11.7 KB
05. Minimal-example-All-Exercises.ipynb	13.2 KB
05. Minimal-example-Exercise-1-Solution.ipynb	70.7 KB
05. Minimal-example-Exercise-2-Solution.ipynb	62.9 KB
05. Minimal-example-Exercise-3.a.Solution.ipynb	69.5 KB
05. Minimal-example-Exercise-3.b.Solution.ipynb	69.3 KB
05. Minimal-example-Exercise-3.c.Solution.ipynb	71.8 KB
05. Minimal-example-Exercise-3.d.Solution.ipynb	86.2 KB
05. Minimal-example-Exercise-4-Solution.ipynb	68.1 KB
05. Minimal-example-Exercise-5-Solution.ipynb	70.5 KB
05. Minimal-example-Exercise-6-Solution.ipynb	63.2 KB
05. Minimal-example-Exercise-6.ipynb	63.2 KB
/46. Deep Learning - TensorFlow 2.0 Introduction/
01. How to Install TensorFlow 2.0.mp4	28.7 MB
01. How to Install TensorFlow 2.0.vtt	6.7 KB
02. TensorFlow Outline and Comparison with Other Libraries.mp4	16.0 MB
02. TensorFlow Outline and Comparison with Other Libraries.vtt	5.6 KB
03. TensorFlow 1 vs TensorFlow 2.mp4	16.0 MB
03. TensorFlow 1 vs TensorFlow 2.vtt	4.1 KB
04. A Note on TensorFlow 2 Syntax.mp4	4.9 MB
04. A Note on TensorFlow 2 Syntax.vtt	1.5 KB
05. Types of File Formats Supporting TensorFlow.mp4	9.3 MB
05. Types of File Formats Supporting TensorFlow.vtt	3.5 KB
06. Outlining the Model with TensorFlow 2.mp4	28.3 MB
06. Outlining the Model with TensorFlow 2.vtt	8.6 KB
07. Interpreting the Result and Extracting the Weights and Bias.mp4	27.2 MB
07. Interpreting the Result and Extracting the Weights and Bias.vtt	6.9 KB
08. Customizing a TensorFlow 2 Model.mp4	17.6 MB
08. Customizing a TensorFlow 2 Model.vtt	4.4 KB
09. Basic NN with TensorFlow Exercises.html	1.3 KB
/assets/
01. Shortcuts-for-Jupyter.pdf	634.0 KB
05. TensorFlow-Minimal-example-Part1.ipynb	1.7 KB
06. TensorFlow-Minimal-example-Part2.ipynb	9.3 KB
07. TensorFlow-Minimal-example-Part3.ipynb	78.4 KB
08. TensorFlow-Minimal-example-complete-with-comments.ipynb	84.3 KB
08. TensorFlow-Minimal-example-complete.ipynb	78.7 KB
09. TensorFlow-Minimal-example-All-exercises.ipynb	85.6 KB
09. TensorFlow-Minimal-example-Exercise-1-Solution.ipynb	28.6 KB
09. TensorFlow-Minimal-Example-Exercise-2-1-Solution.ipynb	85.7 KB
09. TensorFlow-Minimal-Example-Exercise-2-2-Solution.ipynb	79.4 KB
09. TensorFlow-Minimal-Example-Exercise-3-Solution.ipynb	86.5 KB
/47. Deep Learning - Digging Deeper into NNs Introducing Deep Neural Networks/
01. What is a Layer.mp4	5.4 MB
01. What is a Layer.vtt	2.7 KB
02. What is a Deep Net.mp4	9.6 MB
02. What is a Deep Net.vtt	3.3 KB
03. Digging into a Deep Net.mp4	24.8 MB
03. Digging into a Deep Net.vtt	7.1 KB
04. Non-Linearities and their Purpose.mp4	23.6 MB
04. Non-Linearities and their Purpose.vtt	4.3 KB
05. Activation Functions.mp4	9.3 MB
05. Activation Functions.vtt	5.4 KB
06. Activation Functions Softmax Activation.mp4	9.2 MB
06. Activation Functions Softmax Activation.vtt	4.6 KB
07. Backpropagation.mp4	21.3 MB
07. Backpropagation.vtt	4.7 KB
08. Backpropagation Picture.mp4	8.5 MB
08. Backpropagation Picture.vtt	3.9 KB
09. Backpropagation - A Peek into the Mathematics of Optimization.html	0.5 KB
/assets/
01. Course-Notes-Section-6.pdf	958.9 KB
02. Course-Notes-Section-6.pdf	958.9 KB
09. Backpropagation-a-peek-into-the-Mathematics-of-Optimization.pdf	186.8 KB
/48. Deep Learning - Overfitting/
01. What is Overfitting.mp4	11.3 MB
01. What is Overfitting.vtt	6.0 KB
02. Underfitting and Overfitting for Classification.mp4	14.7 MB
02. Underfitting and Overfitting for Classification.vtt	2.9 KB
03. What is Validation.mp4	8.8 MB
03. What is Validation.vtt	5.1 KB
04. Training, Validation, and Test Datasets.mp4	9.9 MB
04. Training, Validation, and Test Datasets.vtt	3.5 KB
05. N-Fold Cross Validation.mp4	6.5 MB
05. N-Fold Cross Validation.vtt	4.5 KB
06. Early Stopping or When to Stop Training.mp4	10.8 MB
06. Early Stopping or When to Stop Training.vtt	7.1 KB
/49. Deep Learning - Initialization/
01. What is Initialization.mp4	9.3 MB
01. What is Initialization.vtt	3.8 KB
02. Types of Simple Initializations.mp4	6.0 MB
02. Types of Simple Initializations.vtt	3.9 KB
03. State-of-the-Art Method - (Xavier) Glorot Initialization.mp4	5.7 MB
03. State-of-the-Art Method - (Xavier) Glorot Initialization.vtt	3.9 KB
/50. Deep Learning - Digging into Gradient Descent and Learning Rate Schedules/
01. Stochastic Gradient Descent.mp4	8.2 MB
01. Stochastic Gradient Descent.vtt	4.9 KB
02. Problems with Gradient Descent.mp4	3.8 MB
02. Problems with Gradient Descent.vtt	3.1 KB
03. Momentum.mp4	5.4 MB
03. Momentum.vtt	3.7 KB
04. Learning Rate Schedules, or How to Choose the Optimal Learning Rate.mp4	18.4 MB
04. Learning Rate Schedules, or How to Choose the Optimal Learning Rate.vtt	6.5 KB
05. Learning Rate Schedules Visualized.mp4	3.3 MB
05. Learning Rate Schedules Visualized.vtt	2.3 KB
06. Adaptive Learning Rate Schedules (AdaGrad and RMSprop ).mp4	8.9 MB
06. Adaptive Learning Rate Schedules (AdaGrad and RMSprop ).vtt	5.7 KB
07. Adam (Adaptive Moment Estimation).mp4	7.5 MB
07. Adam (Adaptive Moment Estimation).vtt	3.5 KB
/51. Deep Learning - Preprocessing/
01. Preprocessing Introduction.mp4	9.7 MB
01. Preprocessing Introduction.vtt	4.2 KB
02. Types of Basic Preprocessing.mp4	3.4 MB
02. Types of Basic Preprocessing.vtt	1.9 KB
03. Standardization.mp4	12.7 MB
03. Standardization.vtt	6.3 KB
04. Preprocessing Categorical Data.mp4	5.7 MB
04. Preprocessing Categorical Data.vtt	2.9 KB
05. Binary and One-Hot Encoding.mp4	9.0 MB
05. Binary and One-Hot Encoding.vtt	5.4 KB
/52. Deep Learning - Classifying on the MNIST Dataset/
01. MNIST The Dataset.mp4	4.8 MB
01. MNIST The Dataset.vtt	3.7 KB
02. MNIST How to Tackle the MNIST.mp4	8.3 MB
02. MNIST How to Tackle the MNIST.vtt	3.7 KB
03. MNIST Importing the Relevant Packages and Loading the Data.mp4	12.8 MB
03. MNIST Importing the Relevant Packages and Loading the Data.vtt	3.1 KB
04. MNIST Preprocess the Data - Create a Validation Set and Scale It.mp4	24.0 MB
04. MNIST Preprocess the Data - Create a Validation Set and Scale It.vtt	6.7 KB
05. MNIST Preprocess the Data - Scale the Test Data - Exercise.html	0.1 KB
06. MNIST Preprocess the Data - Shuffle and Batch.mp4	34.3 MB
06. MNIST Preprocess the Data - Shuffle and Batch.vtt	9.8 KB
07. MNIST Preprocess the Data - Shuffle and Batch - Exercise.html	0.1 KB
08. MNIST Outline the Model.mp4	23.1 MB
08. MNIST Outline the Model.vtt	7.3 KB
09. MNIST Select the Loss and the Optimizer.mp4	11.2 MB
09. MNIST Select the Loss and the Optimizer.vtt	3.1 KB
10. MNIST Learning.mp4	32.5 MB
10. MNIST Learning.vtt	8.1 KB
11. MNIST - Exercises.html	2.0 KB
12. MNIST Testing the Model.mp4	23.7 MB
12. MNIST Testing the Model.vtt	6.1 KB
/assets/
03. TensorFlow-MNIST-Part1-with-comments.ipynb	4.1 KB
05. TensorFlow-MNIST-Part2-with-comments.ipynb	6.5 KB
07. TensorFlow-MNIST-Part3-with-comments.ipynb	8.8 KB
08. TensorFlow-MNIST-Part4-with-comments.ipynb	10.7 KB
09. TensorFlow-MNIST-Part5-with-comments.ipynb	11.2 KB
10. TensorFlow-MNIST-Part6-with-comments.ipynb	12.8 KB
11. 1.TensorFlow-MNIST-Width-Solution.ipynb	15.2 KB
11. 2.TensorFlow-MNIST-Depth-Solution.ipynb	15.7 KB
11. 3.TensorFlow-MNIST-Width-and-Depth-Solution.ipynb	15.7 KB
11. 4.TensorFlow-MNIST-Activation-functions-Part-1-Solution.ipynb	15.5 KB
11. 5.TensorFlow-MNIST-Activation-functions-Part-2-Solution.ipynb	15.1 KB
11. 6.TensorFlow-MNIST-Batch-size-Part-1-Solution.ipynb	15.5 KB
11. 7.TensorFlow-MNIST-Batch-size-Part-2-Solution.ipynb	15.5 KB
11. 8.TensorFlow-MNIST-Learning-rate-Part-1-Solution.ipynb	21.1 KB
11. 9.TensorFlow-MNIST-Learning-rate-Part-2-Solution.ipynb	16.2 KB
11. TensorFlow-MNIST-All-Exercises.ipynb	17.1 KB
11. TensorFlow-MNIST-around-98-percent-accuracy.ipynb	15.4 KB
12. TensorFlow-MNIST-complete-with-comments.ipynb	14.9 KB
12. TensorFlow-MNIST-complete.ipynb	6.9 KB
/53. Deep Learning - Business Case Example/
01. Business Case Exploring the Dataset and Identifying Predictors.mp4	53.8 MB
01. Business Case Exploring the Dataset and Identifying Predictors.vtt	11.3 KB
02. Business Case Outlining the Solution.mp4	3.2 MB
02. Business Case Outlining the Solution.vtt	2.0 KB
03. Business Case Balancing the Dataset.mp4	23.4 MB
03. Business Case Balancing the Dataset.vtt	4.4 KB
04. Business Case Preprocessing the Data.mp4	77.4 MB
04. Business Case Preprocessing the Data.vtt	13.9 KB
05. Business Case Preprocessing the Data - Exercise.html	0.4 KB
06. Business Case Load the Preprocessed Data.mp4	14.5 MB
06. Business Case Load the Preprocessed Data.vtt	4.8 KB
07. Business Case Load the Preprocessed Data - Exercise.html	0.1 KB
08. Business Case Learning and Interpreting the Result.mp4	30.8 MB
08. Business Case Learning and Interpreting the Result.vtt	6.5 KB
09. Business Case Setting an Early Stopping Mechanism.mp4	45.9 MB
09. Business Case Setting an Early Stopping Mechanism.vtt	8.3 KB
10. Setting an Early Stopping Mechanism - Exercise.html	0.2 KB
11. Business Case Testing the Model.mp4	8.6 MB
11. Business Case Testing the Model.vtt	2.2 KB
12. Business Case Final Exercise.html	0.4 KB
/assets/
01. Audiobooks-data.csv	727.8 KB
04. TensorFlow-Audiobooks-Preprocessing-with-comments.ipynb	11.5 KB
04. TensorFlow-Audiobooks-Preprocessing.ipynb	5.7 KB
05. TensorFlow-Audiobooks-Preprocessing-Exercise-Solution.ipynb	10.3 KB
05. TensorFlow-Audiobooks-Preprocessing-Exercise.ipynb	8.8 KB
07. TensorFlow-Audiobooks-Machine-Learning-Part1-with-comments.ipynb	4.7 KB
08. TensorFlow-Audiobooks-Machine-Learning-Part2-with-comments.ipynb	20.2 KB
09. TensorFlow-Audiobooks-Machine-Learning-Part3-with-comments.ipynb	10.3 KB
11. TensorFlow-Audiobooks-Machine-Learning-with-comments.ipynb	12.2 KB
12. TensorFlow-Audiobooks-Machine-Learning-with-comments.ipynb	12.2 KB
/54. Deep Learning - Conclusion/
01. Summary on What You've Learned.mp4	10.3 MB
01. Summary on What You've Learned.vtt	5.6 KB
02. What's Further out there in terms of Machine Learning.mp4	5.0 MB
02. What's Further out there in terms of Machine Learning.vtt	2.8 KB
03. DeepMind and Deep Learning.html	1.1 KB
04. An overview of CNNs.mp4	14.0 MB
04. An overview of CNNs.vtt	6.5 KB
05. An Overview of RNNs.mp4	7.3 MB
05. An Overview of RNNs.vtt	4.1 KB
06. An Overview of non-NN Approaches.mp4	16.9 MB
06. An Overview of non-NN Approaches.vtt	5.9 KB
/55. Appendix Deep Learning - TensorFlow 1 Introduction/
01. READ ME!!!!.html	0.6 KB
02. How to Install TensorFlow 1.mp4	5.2 MB
02. How to Install TensorFlow 1.vtt	3.5 KB
03. A Note on Installing Packages in Anaconda.html	2.3 KB
04. TensorFlow Intro.mp4	17.7 MB
04. TensorFlow Intro.vtt	5.5 KB
05. Actual Introduction to TensorFlow.mp4	9.5 MB
05. Actual Introduction to TensorFlow.vtt	2.4 KB
06. Types of File Formats, supporting Tensors.mp4	9.3 MB
06. Types of File Formats, supporting Tensors.vtt	3.5 KB
07. Basic NN Example with TF Inputs, Outputs, Targets, Weights, Biases.mp4	18.5 MB
07. Basic NN Example with TF Inputs, Outputs, Targets, Weights, Biases.vtt	8.2 KB
08. Basic NN Example with TF Loss Function and Gradient Descent.mp4	14.3 MB
08. Basic NN Example with TF Loss Function and Gradient Descent.vtt	5.0 KB
09. Basic NN Example with TF Model Output.mp4	17.9 MB
09. Basic NN Example with TF Model Output.vtt	8.0 KB
10. Basic NN Example with TF Exercises.html	1.6 KB
/assets/
05. Shortcuts-for-Jupyter.pdf	634.0 KB
06. 5.3.TensorFlow-Minimal-example-Part-1.ipynb	3.4 KB
07. 5.4.TensorFlow-Minimal-example-Part-2.ipynb	6.3 KB
08. 5.5.TensorFlow-Minimal-example-Part-3.ipynb	8.9 KB
09. 5.6.TensorFlow-Minimal-example-complete.ipynb	12.4 KB
10. TensorFlow-Minimal-Example-All-Exercises.ipynb	14.3 KB
10. TensorFlow-Minimal-Example-Exercise-1-Solution.ipynb	24.2 KB
10. TensorFlow-Minimal-Example-Exercise-2-1-Solution.ipynb	26.2 KB
10. TensorFlow-Minimal-Example-Exercise-2-2-Solution.ipynb	26.1 KB
10. TensorFlow-Minimal-Example-Exercise-2-3-Solution.ipynb	51.2 KB
10. TensorFlow-Minimal-Example-Exercise-2-4-Solution.ipynb	22.3 KB
10. TensorFlow-Minimal-Example-Exercise-3-Solution.ipynb	27.4 KB
10. TensorFlow-Minimal-Example-Exercise-4-Solution.ipynb	27.6 KB
/56. Appendix Deep Learning - TensorFlow 1 Classifying on the MNIST Dataset/
01. MNIST What is the MNIST Dataset.mp4	5.0 MB
01. MNIST What is the MNIST Dataset.vtt	3.7 KB
02. MNIST How to Tackle the MNIST.mp4	8.4 MB
02. MNIST How to Tackle the MNIST.vtt	3.9 KB
03. MNIST Relevant Packages.mp4	11.8 MB
03. MNIST Relevant Packages.vtt	2.2 KB
04. MNIST Model Outline.mp4	36.4 MB
04. MNIST Model Outline.vtt	9.4 KB
05. MNIST Loss and Optimization Algorithm.mp4	16.6 MB
05. MNIST Loss and Optimization Algorithm.vtt	3.7 KB
06. Calculating the Accuracy of the Model.mp4	25.6 MB
06. Calculating the Accuracy of the Model.vtt	5.4 KB
07. MNIST Batching and Early Stopping.mp4	9.9 MB
07. MNIST Batching and Early Stopping.vtt	2.9 KB
08. MNIST Learning.mp4	33.4 MB
08. MNIST Learning.vtt	10.7 KB
09. MNIST Results and Testing.mp4	40.0 MB
09. MNIST Results and Testing.vtt	8.4 KB
10. MNIST Exercises.html	2.2 KB
11. MNIST Solutions.html	2.3 KB
/assets/
03. 12.3.TensorFlow-MNIST-with-comments-Part-1.ipynb	4.0 KB
04. 12.4.TensorFlow-MNIST-with-comments-Part-2.ipynb	6.2 KB
05. 12.5.TensorFlow-MNIST-with-comments-Part-3.ipynb	7.5 KB
06. 12.6.TensorFlow-MNIST-with-comments-Part-4.ipynb	8.1 KB
07. 12.7.TensorFlow-MNIST-with-comments-Part-5.ipynb	8.7 KB
08. 12.8.TensorFlow-MNIST-with-comments-Part-6.ipynb	11.8 KB
09. 12.9.TensorFlow-MNIST-with-comments.ipynb	13.3 KB
10. TensorFlow-MNIST-Exercises-All.ipynb	15.8 KB
11. 0.TensorFlow-MNIST-take-note-of-time-Solution.ipynb	14.3 KB
11. 1.TensorFlow-MNIST-Width-Solution.ipynb	14.4 KB
11. 2.TensorFlow-MNIST-Depth-Solution.ipynb	15.2 KB
11. 3.TensorFlow-MNIST-Width-and-Depth-Solution.ipynb	17.2 KB
11. 4.TensorFlow-MNIST-Activation-functions-Part-1-Solution.ipynb	14.7 KB
11. 5.TensorFlow-MNIST-Activation-functions-Part-2-Solution.ipynb	14.3 KB
11. 6.TensorFlow-MNIST-Batch-size-Part-1-Solution.ipynb	14.6 KB
11. 7.TensorFlow-MNIST-Batch-size-Part-2-Solution.ipynb	14.5 KB
11. 8.TensorFlow-MNIST-Learning-rate-Part-1-Solution.ipynb	14.4 KB
11. 9.TensorFlow-MNIST-Learning-rate-Part-2-Solution.ipynb	15.6 KB
11. TensorFlow-MNIST-around-98-percent-accuracy.ipynb	18.1 KB
/57. Appendix Deep Learning - TensorFlow 1 Business Case/
01. Business Case Getting Acquainted with the Dataset.mp4	63.2 MB
01. Business Case Getting Acquainted with the Dataset.vtt	11.2 KB
02. Business Case Outlining the Solution.mp4	4.4 MB
02. Business Case Outlining the Solution.vtt	2.7 KB
03. The Importance of Working with a Balanced Dataset.mp4	28.6 MB
03. The Importance of Working with a Balanced Dataset.vtt	4.5 KB
04. Business Case Preprocessing.mp4	78.0 MB
04. Business Case Preprocessing.vtt	13.9 KB
05. Business Case Preprocessing Exercise.html	0.4 KB
06. Creating a Data Provider.mp4	59.0 MB
06. Creating a Data Provider.vtt	8.5 KB
07. Business Case Model Outline.mp4	44.6 MB
07. Business Case Model Outline.vtt	7.3 KB
08. Business Case Optimization.mp4	28.2 MB
08. Business Case Optimization.vtt	7.1 KB
09. Business Case Interpretation.mp4	19.5 MB
09. Business Case Interpretation.vtt	3.2 KB
10. Business Case Testing the Model.mp4	4.6 MB
10. Business Case Testing the Model.vtt	2.8 KB
11. Business Case A Comment on the Homework.mp4	21.6 MB
11. Business Case A Comment on the Homework.vtt	5.5 KB
12. Business Case Final Exercise.html	0.4 KB
/assets/
01. Audiobooks-data.csv	727.8 KB
03. Audiobooks-data.csv	727.8 KB
04. Audiobooks-data.csv	727.8 KB
04. TensorFlow-Audiobooks-Preprocessing-with-comments.ipynb	11.5 KB
04. TensorFlow-Audiobooks-Preprocessing.ipynb	5.7 KB
05. Audiobooks-data.csv	727.8 KB
05. TensorFlow-Audiobooks-Preprocessing-Exercise-Solution.ipynb	10.3 KB
05. TensorFlow-Audiobooks-Preprocessing-Exercise.ipynb	8.8 KB
07. TensorFlow-Audiobooks-Outlining-the-model-with-comments.ipynb	10.6 KB
07. TensorFlow-Audiobooks-Outlining-the-model.ipynb	9.6 KB
08. TensorFlow-Audiobooks-optimizing-the-algorithm-with-comments.ipynb	13.0 KB
08. TensorFlow-Audiobooks-optimizing-the-algorithm.ipynb	10.9 KB
09. TensorFlow-Audiobooks-optimizing-the-algorithm-with-comments.ipynb	13.0 KB
09. TensorFlow-Audiobooks-optimizing-the-algorithm.ipynb	10.9 KB
11. Audiobooks-data.csv	727.8 KB
11. TensorFlow-Audiobooks-Machine-learning-Homework.ipynb	14.7 KB
11. TensorFlow-Audiobooks-Preprocessing-with-comments.ipynb	11.5 KB
12. Audiobooks-data.csv	727.8 KB
12. TensorFlow-Audiobooks-Machine-learning-Homework.ipynb	14.7 KB
12. TensorFlow-Audiobooks-Preprocessing-with-comments.ipynb	11.5 KB
/58. Software Integration/
01. What are Data, Servers, Clients, Requests, and Responses.mp4	20.5 MB
01. What are Data, Servers, Clients, Requests, and Responses.vtt	6.4 KB
02. What are Data Connectivity, APIs, and Endpoints.mp4	63.1 MB
02. What are Data Connectivity, APIs, and Endpoints.vtt	9.4 KB
03. Taking a Closer Look at APIs.mp4	25.7 MB
03. Taking a Closer Look at APIs.vtt	11.2 KB
04. Communication between Software Products through Text Files.mp4	18.4 MB
04. Communication between Software Products through Text Files.vtt	6.0 KB
05. Software Integration - Explained.mp4	16.8 MB
05. Software Integration - Explained.vtt	7.2 KB
/59. Case Study - What's Next in the Course/
01. Game Plan for this Python, SQL, and Tableau Business Exercise.mp4	20.6 MB
01. Game Plan for this Python, SQL, and Tableau Business Exercise.vtt	5.7 KB
02. The Business Task.mp4	11.8 MB
02. The Business Task.vtt	4.2 KB
03. Introducing the Data Set.mp4	25.4 MB
03. Introducing the Data Set.vtt	4.4 KB
/60. Case Study - Preprocessing the 'Absenteeism_data'/
01. What to Expect from the Following Sections.html	2.5 KB
02. Importing the Absenteeism Data in Python.mp4	20.5 MB
02. Importing the Absenteeism Data in Python.vtt	4.1 KB
03. Checking the Content of the Data Set.mp4	56.6 MB
03. Checking the Content of the Data Set.vtt	7.3 KB
04. Introduction to Terms with Multiple Meanings.mp4	18.9 MB
04. Introduction to Terms with Multiple Meanings.vtt	4.4 KB
05. What's Regression Analysis - a Quick Refresher.html	2.9 KB
06. Using a Statistical Approach towards the Solution to the Exercise.mp4	10.4 MB
06. Using a Statistical Approach towards the Solution to the Exercise.vtt	3.1 KB
07. Dropping a Column from a DataFrame in Python.mp4	43.2 MB
07. Dropping a Column from a DataFrame in Python.vtt	8.4 KB
08. EXERCISE - Dropping a Column from a DataFrame in Python.html	0.9 KB
09. SOLUTION - Dropping a Column from a DataFrame in Python.html	0.1 KB
10. Analyzing the Reasons for Absence.mp4	29.0 MB
10. Analyzing the Reasons for Absence.vtt	6.2 KB
11. Obtaining Dummies from a Single Feature.mp4	73.1 MB
11. Obtaining Dummies from a Single Feature.vtt	10.8 KB
12. EXERCISE - Obtaining Dummies from a Single Feature.html	0.1 KB
13. SOLUTION - Obtaining Dummies from a Single Feature.html	0.1 KB
14. Dropping a Dummy Variable from the Data Set.html	2.4 KB
15. More on Dummy Variables A Statistical Perspective.mp4	6.1 MB
15. More on Dummy Variables A Statistical Perspective.vtt	1.7 KB
16. Classifying the Various Reasons for Absence.mp4	53.8 MB
16. Classifying the Various Reasons for Absence.vtt	10.8 KB
17. Using .concat() in Python.mp4	28.7 MB
17. Using .concat() in Python.vtt	5.3 KB
18. EXERCISE - Using .concat() in Python.html	0.2 KB
19. SOLUTION - Using .concat() in Python.html	0.1 KB
20. Reordering Columns in a Pandas DataFrame in Python.mp4	10.5 MB
20. Reordering Columns in a Pandas DataFrame in Python.vtt	1.9 KB
21. EXERCISE - Reordering Columns in a Pandas DataFrame in Python.html	0.2 KB
22. SOLUTION - Reordering Columns in a Pandas DataFrame in Python.html	0.5 KB
23. Creating Checkpoints while Coding in Jupyter.mp4	18.2 MB
23. Creating Checkpoints while Coding in Jupyter.vtt	3.8 KB
24. EXERCISE - Creating Checkpoints while Coding in Jupyter.html	0.1 KB
25. SOLUTION - Creating Checkpoints while Coding in Jupyter.html	0.1 KB
26. Analyzing the Dates from the Initial Data Set.mp4	42.1 MB
26. Analyzing the Dates from the Initial Data Set.vtt	9.1 KB
27. Extracting the Month Value from the Date Column.mp4	35.5 MB
27. Extracting the Month Value from the Date Column.vtt	8.2 KB
28. Extracting the Day of the Week from the Date Column.mp4	20.1 MB
28. Extracting the Day of the Week from the Date Column.vtt	4.9 KB
29. EXERCISE - Removing the Date Column.html	1.2 KB
30. Analyzing Several Straightforward Columns for this Exercise.mp4	15.0 MB
30. Analyzing Several Straightforward Columns for this Exercise.vtt	4.7 KB
31. Working on Education, Children, and Pets.mp4	28.3 MB
31. Working on Education, Children, and Pets.vtt	6.1 KB
32. Final Remarks of this Section.mp4	14.2 MB
32. Final Remarks of this Section.vtt	2.7 KB
33. A Note on Exporting Your Data as a .csv File.html	0.9 KB
/assets/
01. Absenteeism-data.csv	32.8 KB
01. data-preprocessing-homework.pdf	137.7 KB
01. df-preprocessed.csv	29.8 KB
23. Absenteeism-Exercise-Preprocessing-df-reason-mod.ipynb	4.9 KB
29. Absenteeism-Exercise-Preprocessing-ChP-df-date-reason-mod.ipynb	7.5 KB
29. Absenteeism-Exercise-Preprocessing-LECTURES.ipynb	8.0 MB
29. Absenteeism-Exercise-Removing-the-Date-Column-SOLUTION.ipynb	8.5 KB
32. Absenteeism-Exercise-EXERCISES-and-SOLUTIONS.ipynb	4.2 KB
32. Absenteeism-Exercise-Preprocessing-df-preprocessed.ipynb	8.7 KB
/61. Case Study - Applying Machine Learning to Create the 'absenteeism_module'/
01. Exploring the Problem with a Machine Learning Mindset.mp4	13.6 MB
01. Exploring the Problem with a Machine Learning Mindset.vtt	4.9 KB
02. Creating the Targets for the Logistic Regression.mp4	34.0 MB
02. Creating the Targets for the Logistic Regression.vtt	8.9 KB
03. Selecting the Inputs for the Logistic Regression.mp4	9.1 MB
03. Selecting the Inputs for the Logistic Regression.vtt	3.7 KB
04. Standardizing the Data.mp4	15.9 MB
04. Standardizing the Data.vtt	4.4 KB
05. Splitting the Data for Training and Testing.mp4	37.8 MB
05. Splitting the Data for Training and Testing.vtt	8.7 KB
06. Fitting the Model and Assessing its Accuracy.mp4	16.0 MB
06. Fitting the Model and Assessing its Accuracy.vtt	7.5 KB
07. Creating a Summary Table with the Coefficients and Intercept.mp4	28.3 MB
07. Creating a Summary Table with the Coefficients and Intercept.vtt	6.5 KB
08. Interpreting the Coefficients for Our Problem.mp4	43.1 MB
08. Interpreting the Coefficients for Our Problem.vtt	8.7 KB
09. Standardizing only the Numerical Variables (Creating a Custom Scaler).mp4	17.7 MB
09. Standardizing only the Numerical Variables (Creating a Custom Scaler).vtt	5.4 KB
10. Interpreting the Coefficients of the Logistic Regression.mp4	15.9 MB
10. Interpreting the Coefficients of the Logistic Regression.vtt	7.7 KB
11. Backward Elimination or How to Simplify Your Model.mp4	33.4 MB
11. Backward Elimination or How to Simplify Your Model.vtt	5.5 KB
12. Testing the Model We Created.mp4	33.1 MB
12. Testing the Model We Created.vtt	6.7 KB
13. Saving the Model and Preparing it for Deployment.mp4	26.8 MB
13. Saving the Model and Preparing it for Deployment.vtt	5.9 KB
14. ARTICLE - A Note on 'pickling'.html	2.2 KB
15. EXERCISE - Saving the Model (and Scaler).html	0.3 KB
16. Preparing the Deployment of the Model through a Module.mp4	29.9 MB
16. Preparing the Deployment of the Model through a Module.vtt	6.0 KB
/assets/
01. Absenteeism-preprocessed.csv	29.8 KB
/62. Case Study - Loading the 'absenteeism_module'/
01. Are You Sure You're All Set.html	0.5 KB
02. Deploying the 'absenteeism_module' - Part I.mp4	20.6 MB
02. Deploying the 'absenteeism_module' - Part I.vtt	5.1 KB
03. Deploying the 'absenteeism_module' - Part II.mp4	47.3 MB
03. Deploying the 'absenteeism_module' - Part II.vtt	8.2 KB
04. Exporting the Obtained Data Set as a .csv.html	1.0 KB
/assets/
01. Absenteeism-Exercise-Integration.ipynb	63.8 KB
01. absenteeism-module.py	6.8 KB
01. Absenteeism-new-data.csv	1.9 KB
01. model	1.0 KB
01. scaler	1.9 KB
04. Absenteeism-Exercise-Deploying-the-absenteeism-module.ipynb	1.0 KB
/63. Case Study - Analyzing the Predicted Outputs in Tableau/
01. EXERCISE - Age vs Probability.html	0.4 KB
02. Analyzing Age vs Probability in Tableau.mp4	40.6 MB
02. Analyzing Age vs Probability in Tableau.vtt	10.5 KB
03. EXERCISE - Reasons vs Probability.html	0.4 KB
04. Analyzing Reasons vs Probability in Tableau.mp4	42.2 MB
04. Analyzing Reasons vs Probability in Tableau.vtt	9.9 KB
05. EXERCISE - Transportation Expense vs Probability.html	0.6 KB
06. Analyzing Transportation Expense vs Probability in Tableau.mp4	17.3 MB
06. Analyzing Transportation Expense vs Probability in Tableau.vtt	7.8 KB
/assets/
01. Absenteeism-predictions.csv	2.2 KB
02. Absenteeism-predictions.csv	2.2 KB
/64. Appendix - Additional Python Tools/
01. Using the .format() Method.mp4	26.9 MB
01. Using the .format() Method.vtt	13.0 KB
02. Iterating Over Range Objects.mp4	13.2 MB
02. Iterating Over Range Objects.vtt	6.6 KB
03. Introduction to Nested For Loops.mp4	12.8 MB
03. Introduction to Nested For Loops.vtt	8.7 KB
04. Triple Nested For Loops.mp4	34.6 MB
04. Triple Nested For Loops.vtt	8.7 KB
05. List Comprehensions.mp4	45.3 MB
05. List Comprehensions.vtt	13.1 KB
06. Anonymous (Lambda) Functions.mp4	23.9 MB
06. Anonymous (Lambda) Functions.vtt	10.7 KB
/assets/
01. Additional-Python-Tools-Exercises.ipynb	11.7 KB
01. Additional-Python-Tools-Lectures.ipynb	13.8 KB
01. Additional-Python-Tools-Solutions.ipynb	26.1 KB
06. Additional-Python-Tools-Exercises.ipynb	11.7 KB
06. Additional-Python-Tools-Lectures.ipynb	13.8 KB
06. Additional-Python-Tools-Solutions.ipynb	26.1 KB
/65. Appendix - pandas Fundamentals/
01. Introduction to pandas Series.mp4	26.2 MB
01. Introduction to pandas Series.vtt	11.1 KB
02. A Note on Completing the Upcoming Coding Exercises.html	3.0 KB
03. Working with Methods in Python - Part I.mp4	13.9 MB
03. Working with Methods in Python - Part I.vtt	7.4 KB
04. Working with Methods in Python - Part II.mp4	9.4 MB
04. Working with Methods in Python - Part II.vtt	4.0 KB
05. Parameters and Arguments in pandas.mp4	22.2 MB
05. Parameters and Arguments in pandas.vtt	5.9 KB
06. Using .unique() and .nunique().mp4	25.5 MB
06. Using .unique() and .nunique().vtt	6.0 KB
07. Using .sort_values().mp4	16.0 MB
07. Using .sort_values().vtt	5.7 KB
08. Introduction to pandas DataFrames - Part I.mp4	13.1 MB
08. Introduction to pandas DataFrames - Part I.vtt	7.5 KB
09. Introduction to pandas DataFrames - Part II.mp4	18.7 MB
09. Introduction to pandas DataFrames - Part II.vtt	8.2 KB
10. pandas DataFrames - Common Attributes.mp4	26.9 MB
10. pandas DataFrames - Common Attributes.vtt	6.7 KB
11. Data Selection in pandas DataFrames.mp4	39.1 MB
11. Data Selection in pandas DataFrames.vtt	10.8 KB
12. pandas DataFrames - Indexing with .iloc[].mp4	33.8 MB
12. pandas DataFrames - Indexing with .iloc[].vtt	8.5 KB
13. pandas DataFrames - Indexing with .loc[].mp4	21.7 MB
13. pandas DataFrames - Indexing with .loc[].vtt	5.7 KB
/assets/
01. Lending-company.csv	115.1 KB
01. Location.csv	13.8 KB
01. pandas-Fundamentals-Exercises.ipynb	31.7 KB
01. pandas-Fundamentals-Lectures.ipynb	21.8 KB
01. pandas-Fundamentals-Solutions.ipynb	121.2 KB
01. Region.csv	10.5 KB
01. Sales-products.csv	155.9 KB
13. Lending-company.csv	115.1 KB
13. Location.csv	13.8 KB
13. pandas-Fundamentals-Exercises.ipynb	31.7 KB
13. pandas-Fundamentals-Lectures.ipynb	21.8 KB
13. pandas-Fundamentals-Solutions.ipynb	121.2 KB
13. Region.csv	10.5 KB
13. Sales-products.csv	155.9 KB
/66. Bonus Lecture/
01. Bonus Lecture Next Steps.html	4.4 KB
/assets/
01. 365-Data-Science-Data-Science-Interview-Questions-Guide.pdf	16.3 MB
Total files 1493