Tutorialsplanet NET Udemy Complete Data Science Training with Python for Data Analysis

Tutorialsplanet NET Udemy Complete Data Science Training with Python for Data Analysis

Name	[Tutorialsplanet.NET] Udemy - Complete Data Science Training with Python for Data Analysis	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	2.4 GB
Total Files	248
Hash	13F2A54C3007F7D6E34CE9E3CBB37BEB7E3E747F

/1. Introduction to the Data Science in Python Bootcamp/
1. What is Data Science.mp4	8.8 MB
1. What is Data Science.vtt	4.1 KB
2. Introduction to the Course & Instructor.mp4	31.1 MB
2. Introduction to the Course & Instructor.vtt	13.8 KB
3. Data For the Course.html	0.1 KB
3.1 scriptsLecture.zip.zip	323.0 MB
4. Introduction to the Python Data Science Tool.mp4	26.2 MB
4. Introduction to the Python Data Science Tool.vtt	10.4 KB
5. For Mac Users.mp4	10.7 MB
5. For Mac Users.vtt	4.0 KB
6. Introduction to the Python Data Science Environment.mp4	42.3 MB
6. Introduction to the Python Data Science Environment.vtt	17.6 KB
7. Some Miscellaneous IPython Usage Facts.mp4	12.6 MB
7. Some Miscellaneous IPython Usage Facts.vtt	4.7 KB
8. Online iPython Interpreter.mp4	8.1 MB
8. Online iPython Interpreter.vtt	3.5 KB
9. Conclusion to Section 1.mp4	6.8 MB
9. Conclusion to Section 1.vtt	3.1 KB
/10. Unsupervised Learning in Python/
1. Unsupervised Classification- Some Basic Ideas.mp4	6.5 MB
1. Unsupervised Classification- Some Basic Ideas.vtt	1.9 KB
10. Principal Component Analysis (PCA)-Practical Implementation.mp4	9.5 MB
10. Principal Component Analysis (PCA)-Practical Implementation.vtt	4.3 KB
11. Conclusions to Section 10.mp4	5.8 MB
11. Conclusions to Section 10.vtt	2.5 KB
2. KMeans-theory.mp4	5.4 MB
2. KMeans-theory.vtt	2.6 KB
3. KMeans-implementation on the iris data.mp4	20.5 MB
3. KMeans-implementation on the iris data.vtt	7.8 KB
4. Quantifying KMeans Clustering Performance.mp4	10.0 MB
4. Quantifying KMeans Clustering Performance.vtt	4.5 KB
5. KMeans Clustering with Real Data.mp4	12.7 MB
5. KMeans Clustering with Real Data.vtt	4.6 KB
6. How Do We Select the Number of Clusters.mp4	20.0 MB
6. How Do We Select the Number of Clusters.vtt	4.3 KB
7. Hierarchical Clustering-theory.mp4	10.7 MB
7. Hierarchical Clustering-theory.vtt	5.1 KB
8. Hierarchical Clustering-practical.mp4	30.8 MB
8. Hierarchical Clustering-practical.vtt	9.8 KB
9. Principal Component Analysis (PCA)-Theory.mp4	6.2 MB
9. Principal Component Analysis (PCA)-Theory.vtt	3.0 KB
/11. Supervised Learning/
1. What is This Section About.mp4	26.1 MB
1. What is This Section About.vtt	11.8 KB
10. knn-Classification.mp4	19.1 MB
10. knn-Classification.vtt	8.2 KB
11. knn-Regression.mp4	8.8 MB
11. knn-Regression.vtt	4.0 KB
12. Gradient Boosting-classification.mp4	15.8 MB
12. Gradient Boosting-classification.vtt	6.2 KB
13. Gradient Boosting-regression.mp4	11.4 MB
13. Gradient Boosting-regression.vtt	3.8 KB
14. Voting Classifier.mp4	10.0 MB
14. Voting Classifier.vtt	3.9 KB
15. Conclusions to Section 11.mp4	7.6 MB
15. Conclusions to Section 11.vtt	3.0 KB
16. Section 11 Quiz.html	0.2 KB
2. Data Preparation for Supervised Learning.mp4	29.7 MB
2. Data Preparation for Supervised Learning.vtt	10.3 KB
3. Pointers on Evaluating the Accuracy of Classification and Regression Modelling.mp4	25.2 MB
3. Pointers on Evaluating the Accuracy of Classification and Regression Modelling.vtt	10.7 KB
4. Using Logistic Regression as a Classification Model.mp4	21.6 MB
4. Using Logistic Regression as a Classification Model.vtt	8.9 KB
5. RF-Classification.mp4	29.9 MB
5. RF-Classification.vtt	12.5 KB
6. RF-Regression.mp4	24.8 MB
6. RF-Regression.vtt	10.0 KB
7. SVM- Linear Classification.mp4	7.7 MB
7. SVM- Linear Classification.vtt	3.3 KB
8. SVM- Non Linear Classification.mp4	5.4 MB
8. SVM- Non Linear Classification.vtt	2.4 KB
9. Support Vector Regression.mp4	10.7 MB
9. Support Vector Regression.vtt	4.4 KB
/12. Artificial Neural Networks (ANN) and Deep Learning (DL)/
1. Theory Behind ANN and DNN.mp4	23.7 MB
1. Theory Behind ANN and DNN.vtt	10.1 KB
10. Specify the Activation Function.mp4	6.5 MB
10. Specify the Activation Function.vtt	2.2 KB
11. H2O Deep Learning For Predictions.mp4	12.6 MB
11. H2O Deep Learning For Predictions.vtt	5.3 KB
12. Conclusions to Section 12.mp4	5.4 MB
12. Conclusions to Section 12.vtt	2.2 KB
13. Section 12 Quiz.html	0.2 KB
2. Perceptrons for Binary Classification.mp4	10.5 MB
2. Perceptrons for Binary Classification.vtt	4.8 KB
3. Getting Started with ANN-binary classification.mp4	8.9 MB
3. Getting Started with ANN-binary classification.vtt	3.6 KB
4. Multi-label classification with MLP.mp4	14.1 MB
4. Multi-label classification with MLP.vtt	4.9 KB
5. Regression with MLP.mp4	9.5 MB
5. Regression with MLP.vtt	3.6 KB
6. MLP with PCA on a Large Dataset.mp4	20.2 MB
6. MLP with PCA on a Large Dataset.vtt	7.8 KB
7. Start With Deep Neural Network (DNN).html	0.2 KB
8. Start with H20.mp4	12.7 MB
8. Start with H20.vtt	4.4 KB
9. Default H2O Deep Learning Algorithm.mp4	8.6 MB
9. Default H2O Deep Learning Algorithm.vtt	3.4 KB
/13. Miscellaneous Lectures & Information/
1. Data For This Section.html	0.1 KB
2. Read in Data from Online CSV.mp4	7.0 MB
2. Read in Data from Online CSV.vtt	4.0 KB
3. Read Data from a Database.mp4	12.9 MB
3. Read Data from a Database.vtt	8.0 KB
4. Naive Bayes Classification.mp4	10.3 MB
4. Naive Bayes Classification.vtt	7.0 KB
5. Data Imputation.mp4	59.2 MB
5. Data Imputation.vtt	9.2 KB
/2. Introduction to Python Pre-Requisites for Data Science/
1. Rationale Behind This Section.html	0.4 KB
2. Different Types of Data Used in Statistical & ML Analysis.mp4	9.8 MB
2. Different Types of Data Used in Statistical & ML Analysis.vtt	3.7 KB
3. Different Types of Data Used Programatically.mp4	8.1 MB
3. Different Types of Data Used Programatically.vtt	3.1 KB
4. Python Data Science Packages To Be Used.mp4	8.3 MB
4. Python Data Science Packages To Be Used.vtt	3.9 KB
5. Conclusions to Section 2.mp4	5.1 MB
5. Conclusions to Section 2.vtt	2.5 KB
/3. Introduction to Numpy/
1. Numpy Introduction.mp4	9.1 MB
1. Numpy Introduction.vtt	3.9 KB
10. Conclusion to Section 3.mp4	6.5 MB
10. Conclusion to Section 3.vtt	2.6 KB
11. Section 3 Quiz.html	0.2 KB
2. Create Numpy Arrays.mp4	21.9 MB
2. Create Numpy Arrays.vtt	6.1 KB
3. Numpy Operations.mp4	38.5 MB
3. Numpy Operations.vtt	15.3 KB
4. Matrix Arithmetic and Linear Systems.mp4	16.6 MB
4. Matrix Arithmetic and Linear Systems.vtt	6.6 KB
5. Numpy for Basic Vector Arithmetric.mp4	12.3 MB
5. Numpy for Basic Vector Arithmetric.vtt	3.9 KB
6. Numpy for Basic Matrix Arithmetic.mp4	14.6 MB
6. Numpy for Basic Matrix Arithmetic.vtt	5.3 KB
7. Broadcasting with Numpy.mp4	9.4 MB
7. Broadcasting with Numpy.vtt	3.9 KB
8. Solve Equations with Numpy.mp4	12.0 MB
8. Solve Equations with Numpy.vtt	4.3 KB
9. Numpy for Statistical Operation.mp4	15.7 MB
9. Numpy for Statistical Operation.vtt	6.9 KB
/4. Introduction to Pandas/
1. Data Structures in Python.mp4	26.3 MB
1. Data Structures in Python.vtt	10.3 KB
2. Read in Data.html	0.2 KB
3. Read in CSV Data Using Pandas.mp4	16.1 MB
3. Read in CSV Data Using Pandas.vtt	5.9 KB
4. Read in Excel Data Using Pandas.mp4	11.9 MB
4. Read in Excel Data Using Pandas.vtt	3.9 KB
5. Reading in JSON Data.mp4	19.6 MB
5. Reading in JSON Data.vtt	3.1 KB
6. Read in HTML Data.mp4	53.8 MB
6. Read in HTML Data.vtt	11.4 KB
7. Conclusion to Section 4.mp4	5.7 MB
7. Conclusion to Section 4.vtt	2.3 KB
/5. Data Pre-ProcessingWrangling/
1. Rationale behind this section.mp4	8.5 MB
1. Rationale behind this section.vtt	4.7 KB
10. Rank and Sort Data.mp4	25.5 MB
10. Rank and Sort Data.vtt	7.5 KB
11. Concatenate.mp4	24.9 MB
11. Concatenate.vtt	8.2 KB
12. Merging and Joining Data Frames.mp4	30.2 MB
12. Merging and Joining Data Frames.vtt	10.9 KB
13. Conclusion to Section 5.mp4	5.7 MB
13. Conclusion to Section 5.vtt	2.3 KB
2. Removing NAsNo Values From Our Data.mp4	20.2 MB
2. Removing NAsNo Values From Our Data.vtt	6.5 KB
3. Basic Data Handling Starting with Conditional Data Selection.mp4	15.6 MB
3. Basic Data Handling Starting with Conditional Data Selection.vtt	4.2 KB
4. Drop ColumnRow.mp4	16.5 MB
4. Drop ColumnRow.vtt	4.5 KB
5. Subset and Index Data.mp4	29.4 MB
5. Subset and Index Data.vtt	8.0 KB
6. Basic Data Grouping Based on Qualitative Attributes.mp4	27.9 MB
6. Basic Data Grouping Based on Qualitative Attributes.vtt	8.5 KB
7. Crosstabulation.mp4	11.4 MB
7. Crosstabulation.vtt	3.9 KB
8. Reshaping.mp4	25.4 MB
8. Reshaping.vtt	9.8 KB
9. Pivoting.mp4	25.2 MB
9. Pivoting.vtt	8.6 KB
/6. Introduction to Data Visualizations/
1. What is Data Visualization.mp4	21.7 MB
1. What is Data Visualization.vtt	10.0 KB
2. Some Theoretical Principles Behind Data Visualization.mp4	17.4 MB
2. Some Theoretical Principles Behind Data Visualization.vtt	7.3 KB
3. Histograms-Visualize the Distribution of Continuous Numerical Variables.mp4	30.8 MB
3. Histograms-Visualize the Distribution of Continuous Numerical Variables.vtt	12.2 KB
4. Boxplots-Visualize the Distribution of Continuous Numerical Variables.mp4	14.1 MB
4. Boxplots-Visualize the Distribution of Continuous Numerical Variables.vtt	5.6 KB
5. Scatter Plot-Visualize the Relationship Between 2 Continuous Variables.mp4	31.3 MB
5. Scatter Plot-Visualize the Relationship Between 2 Continuous Variables.vtt	12.5 KB
6. Barplot.mp4	56.4 MB
6. Barplot.vtt	22.9 KB
7. Pie Chart.mp4	13.4 MB
7. Pie Chart.vtt	5.7 KB
8. Line Chart.mp4	38.9 MB
8. Line Chart.vtt	12.3 KB
9. Conclusions to Section 6.mp4	6.1 MB
9. Conclusions to Section 6.vtt	2.3 KB
/7. Statistical Data Analysis-Basic/
1. What is Statistical Data Analysis.mp4	26.5 MB
1. What is Statistical Data Analysis.vtt	9.8 KB
10. Standard Normal Distribution and Z-scores.mp4	10.3 MB
10. Standard Normal Distribution and Z-scores.vtt	4.3 KB
11. Confidence Interval-Theory.mp4	14.4 MB
11. Confidence Interval-Theory.vtt	6.0 KB
12. Confidence Interval-Calculation.mp4	14.3 MB
12. Confidence Interval-Calculation.vtt	5.9 KB
13. Conclusions to Section 7.mp4	4.0 MB
13. Conclusions to Section 7.vtt	1.6 KB
2. Some Pointers on Collecting Data for Statistical Studies.mp4	21.9 MB
2. Some Pointers on Collecting Data for Statistical Studies.vtt	9.3 KB
3. Some Pointers on Exploring Quantitative Data.html	0.5 KB
4. Explore the Quantitative Data Descriptive Statistics.mp4	18.2 MB
4. Explore the Quantitative Data Descriptive Statistics.vtt	7.8 KB
5. Grouping & Summarizing Data by Categories.mp4	34.7 MB
5. Grouping & Summarizing Data by Categories.vtt	10.5 KB
6. Visualize Descriptive Statistics-Boxplots.mp4	12.1 MB
6. Visualize Descriptive Statistics-Boxplots.vtt	5.4 KB
7. Common Terms Relating to Descriptive Statistics.mp4	12.2 MB
7. Common Terms Relating to Descriptive Statistics.vtt	5.7 KB
8. Data Distribution- Normal Distribution.mp4	10.1 MB
8. Data Distribution- Normal Distribution.vtt	4.0 KB
9. Check for Normal Distribution.mp4	17.3 MB
9. Check for Normal Distribution.vtt	5.8 KB
/8. Statistical Inference & Relationship Between Variables/
1. What is Hypothesis Testing.mp4	14.1 MB
1. What is Hypothesis Testing.vtt	6.0 KB
10. Polynomial Regression.mp4	9.7 MB
10. Polynomial Regression.vtt	3.8 KB
11. GLM Generalized Linear Model.mp4	12.4 MB
11. GLM Generalized Linear Model.vtt	5.3 KB
12. Logistic Regression.mp4	30.2 MB
12. Logistic Regression.vtt	11.4 KB
13. Conclusions to Section 8.mp4	5.2 MB
13. Conclusions to Section 8.vtt	2.1 KB
14. Section 8 Quiz.html	0.2 KB
2. Test the Difference Between Two Groups.mp4	18.6 MB
2. Test the Difference Between Two Groups.vtt	7.5 KB
3. Test the Difference Between More Than Two Groups.mp4	29.7 MB
3. Test the Difference Between More Than Two Groups.vtt	11.2 KB
4. Explore the Relationship Between Two Quantitative Variables.mp4	9.9 MB
4. Explore the Relationship Between Two Quantitative Variables.vtt	4.5 KB
5. Correlation Analysis.mp4	21.7 MB
5. Correlation Analysis.vtt	8.8 KB
6. Linear Regression-Theory.mp4	26.1 MB
6. Linear Regression-Theory.vtt	10.1 KB
7. Linear Regression-Implementation in Python.mp4	31.6 MB
7. Linear Regression-Implementation in Python.vtt	11.8 KB
8. Conditions of Linear Regression.mp4	3.1 MB
8. Conditions of Linear Regression.vtt	1.9 KB
9. Conditions of Linear Regression-Check in Python.mp4	35.0 MB
9. Conditions of Linear Regression-Check in Python.vtt	12.9 KB
/9. Machine Learning for Data Science/
1. How is Machine Learning Different from Statistical Data Analysis.mp4	14.4 MB
1. How is Machine Learning Different from Statistical Data Analysis.vtt	6.3 KB
2. What is Machine Learning (ML) About Some Theoretical Pointers.mp4	16.5 MB
2. What is Machine Learning (ML) About Some Theoretical Pointers.vtt	6.7 KB
/
[Tutorialsplanet.NET].url	0.1 KB
Total files 248