GigaCourse Com Udemy Python for Data Science Machine Learning from

GigaCourse Com Udemy Python for Data Science Machine Learning from

Name	[GigaCourse.Com] Udemy - Python for Data Science & Machine Learning from A-Z	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	7.9 GB
Total Files	298
Last Seen	2025-06-16 00:06
Hash	E4166DCF5CE4A8C75A656340D075DD43323182F1

/0. Websites you may like/
[CourseClub.ME].url	0.1 KB
[GigaCourse.Com].url	0.0 KB
/1. Introduction/
1. Who is This Course For.mp4	18.0 MB
1. Who is This Course For.srt	4.0 KB
2. Data Science + Machine Learning Marketplace.mp4	49.2 MB
2. Data Science + Machine Learning Marketplace.srt	10.7 KB
3. Data Science Job Opportunities.mp4	30.9 MB
3. Data Science Job Opportunities.srt	7.0 KB
4. Data Science Job Roles.mp4	83.7 MB
4. Data Science Job Roles.srt	16.1 KB
5. What is a Data Scientist.mp4	133.7 MB
5. What is a Data Scientist.srt	27.5 KB
6. How To Get a Data Science Job.mp4	137.6 MB
6. How To Get a Data Science Job.srt	31.4 KB
7. Data Science Projects Overview.mp4	83.3 MB
7. Data Science Projects Overview.srt	19.5 KB
/10. Data Loading & Exploration/
1. Exploratory Data Analysis.mp4	53.0 MB
1. Exploratory Data Analysis.srt	19.5 KB
/11. Data Cleaning/
1. Feature Scaling.mp4	20.3 MB
1. Feature Scaling.srt	11.9 KB
2. Data Cleaning.mp4	31.7 MB
2. Data Cleaning.srt	11.8 KB
/12. Feature Selecting and Engineering/
1. Feature Engineering.mp4	19.3 MB
1. Feature Engineering.srt	9.7 KB
/13. Linear and Logistic Regression/
1. Linear Regression Intro.mp4	32.3 MB
1. Linear Regression Intro.srt	12.5 KB
2. Gradient Descent.mp4	16.7 MB
2. Gradient Descent.srt	8.6 KB
3. Linear Regression + Correlation Methods.mp4	115.7 MB
3. Linear Regression + Correlation Methods.srt	39.5 KB
4. Linear Regression Implementation.mp4	18.7 MB
4. Linear Regression Implementation.srt	7.0 KB
5. Logistic Regression.mp4	9.3 MB
5. Logistic Regression.srt	5.1 KB
/14. K Nearest Neighbors/
1. KNN Overview.mp4	13.5 MB
1. KNN Overview.srt	4.4 KB
10. Feature scaling in KNN.mp4	51.8 MB
10. Feature scaling in KNN.srt	8.3 KB
11. Curse of dimensionality.mp4	48.2 MB
11. Curse of dimensionality.srt	9.8 KB
12. KNN use cases.mp4	30.3 MB
12. KNN use cases.srt	5.0 KB
13. KNN pros and cons.mp4	31.9 MB
13. KNN pros and cons.srt	7.9 KB
2. parametric vs non-parametric models.mp4	16.4 MB
2. parametric vs non-parametric models.srt	4.8 KB
3. EDA on Iris Dataset.mp4	169.7 MB
3. EDA on Iris Dataset.srt	32.4 KB
4. The KNN Intuition.mp4	8.5 MB
4. The KNN Intuition.srt	3.1 KB
5. Implement the KNN algorithm from scratch.mp4	91.2 MB
5. Implement the KNN algorithm from scratch.srt	17.6 KB
6. Compare the result with the sklearn library.mp4	25.8 MB
6. Compare the result with the sklearn library.srt	5.2 KB
7. Hyperparameter tuning using the cross-validation.mp4	94.7 MB
7. Hyperparameter tuning using the cross-validation.srt	15.0 KB
8. The decision boundary visualization.mp4	17.8 MB
8. The decision boundary visualization.srt	7.2 KB
9. Manhattan vs Euclidean Distance.mp4	32.0 MB
9. Manhattan vs Euclidean Distance.srt	7.9 KB
/15. Decision Trees/
1. Decision Trees Section Overview.mp4	17.3 MB
1. Decision Trees Section Overview.srt	5.7 KB
10. Visualizing the tree.mp4	71.5 MB
10. Visualizing the tree.srt	15.4 KB
11. Plot the features importance.mp4	33.2 MB
11. Plot the features importance.srt	7.9 KB
12. Decision Trees Hyper-parameters.mp4	85.2 MB
12. Decision Trees Hyper-parameters.srt	16.5 KB
13. Pruning.mp4	118.5 MB
13. Pruning.srt	24.9 KB
14. [Optional] Gain Ration.mp4	20.1 MB
14. [Optional] Gain Ration.srt	3.8 KB
15. Decision Trees Pros and Cons.mp4	50.1 MB
15. Decision Trees Pros and Cons.srt	10.9 KB
16. [Project] Predict whether income exceeds $50Kyr - Overview.mp4	15.8 MB
16. [Project] Predict whether income exceeds $50Kyr - Overview.srt	3.7 KB
2. EDA on Adult Dataset.mp4	129.2 MB
2. EDA on Adult Dataset.srt	24.3 KB
3. What is Entropy and Information Gain.mp4	142.7 MB
3. What is Entropy and Information Gain.srt	30.0 KB
4. The Decision Tree ID3 algorithm from scratch Part 1.mp4	89.4 MB
4. The Decision Tree ID3 algorithm from scratch Part 1.srt	15.3 KB
5. The Decision Tree ID3 algorithm from scratch Part 2.mp4	67.1 MB
5. The Decision Tree ID3 algorithm from scratch Part 2.srt	10.9 KB
6. The Decision Tree ID3 algorithm from scratch Part 3.mp4	35.0 MB
6. The Decision Tree ID3 algorithm from scratch Part 3.srt	5.9 KB
7. ID3 - Putting Everything Together.mp4	191.3 MB
7. ID3 - Putting Everything Together.srt	31.8 KB
8. Evaluating our ID3 implementation.mp4	127.9 MB
8. Evaluating our ID3 implementation.srt	25.1 KB
9. Compare with Sklearn implementation.mp4	68.8 MB
9. Compare with Sklearn implementation.srt	12.6 KB
/16. Ensemble Learning and Random Forests/
1. Ensemble Learning Section Overview.mp4	16.9 MB
1. Ensemble Learning Section Overview.srt	5.3 KB
10. Random Forests Pros and Cons.mp4	20.6 MB
10. Random Forests Pros and Cons.srt	8.0 KB
11. What is Boosting.mp4	37.2 MB
11. What is Boosting.srt	7.0 KB
12. AdaBoost Part 1.mp4	26.8 MB
12. AdaBoost Part 1.srt	5.6 KB
13. AdaBoost Part 2.mp4	90.1 MB
13. AdaBoost Part 2.srt	21.4 KB
2. What is Ensemble Learning.mp4	96.4 MB
2. What is Ensemble Learning.srt	17.8 KB
3. What is Bootstrap Sampling.mp4	58.6 MB
3. What is Bootstrap Sampling.srt	11.4 KB
4. What is Bagging.mp4	30.9 MB
4. What is Bagging.srt	7.9 KB
5. Out-of-Bag Error (OOB Error).mp4	44.1 MB
5. Out-of-Bag Error (OOB Error).srt	10.2 KB
6. Implementing Random Forests from scratch Part 1.mp4	212.4 MB
6. Implementing Random Forests from scratch Part 1.srt	30.8 KB
7. Implementing Random Forests from scratch Part 2.mp4	53.0 MB
7. Implementing Random Forests from scratch Part 2.srt	8.5 KB
8. Compare with sklearn implementation.mp4	29.0 MB
8. Compare with sklearn implementation.srt	5.1 KB
9. Random Forests Hyper-Parameters.mp4	41.6 MB
9. Random Forests Hyper-Parameters.srt	6.1 KB
[CourseClub.Me].url	0.1 KB
[GigaCourse.Com].url	0.0 KB
/17. Support Vector Machines/
1. SVM Outline.mp4	37.0 MB
1. SVM Outline.srt	7.6 KB
10. SMV - Project Overview.mp4	41.5 MB
10. SMV - Project Overview.srt	6.4 KB
2. SVM intuition.mp4	51.2 MB
2. SVM intuition.srt	16.4 KB
3. Hard vs Soft Margins.mp4	68.8 MB
3. Hard vs Soft Margins.srt	19.4 KB
4. C hyper-parameter.mp4	22.1 MB
4. C hyper-parameter.srt	5.8 KB
5. Kernel Trick.mp4	80.8 MB
5. Kernel Trick.srt	18.6 KB
6. SVM - Kernel Types.mp4	132.5 MB
6. SVM - Kernel Types.srt	27.4 KB
7. SVM with Linear Dataset (Iris).mp4	106.5 MB
7. SVM with Linear Dataset (Iris).srt	20.3 KB
8. SVM with Non-linear Dataset.mp4	117.0 MB
8. SVM with Non-linear Dataset.srt	18.8 KB
9. SVM with Regression.mp4	26.2 MB
9. SVM with Regression.srt	8.2 KB
/18. K-means/
1. Unsupervised Machine Learning Intro.mp4	105.8 MB
1. Unsupervised Machine Learning Intro.srt	30.1 KB
1.1 Unsupervised Learning.pdf	651.8 KB
2. Unsupervised Machine Learning Continued.mp4	87.2 MB
2. Unsupervised Machine Learning Continued.srt	29.9 KB
3. Representing Clusters.mp4	114.9 MB
3. Representing Clusters.srt	29.0 KB
/19. PCA/
1. PCA Section Overview.mp4	33.3 MB
1. PCA Section Overview.srt	7.2 KB
10. PCA - Feature Scaling and Screen Plot.mp4	71.5 MB
10. PCA - Feature Scaling and Screen Plot.srt	14.7 KB
11. PCA - Supervised vs Unsupervised.mp4	37.5 MB
11. PCA - Supervised vs Unsupervised.srt	7.3 KB
12. PCA - Visualization.mp4	71.3 MB
12. PCA - Visualization.srt	11.2 KB
2. What is PCA.mp4	49.6 MB
2. What is PCA.srt	14.9 KB
3. PCA Drawbacks.mp4	20.4 MB
3. PCA Drawbacks.srt	5.0 KB
4. PCA Algorithm Steps (Mathematics).mp4	60.5 MB
4. PCA Algorithm Steps (Mathematics).srt	19.0 KB
5. Covariance Matrix vs SVD.mp4	40.6 MB
5. Covariance Matrix vs SVD.srt	6.7 KB
6. PCA - Main Applications.mp4	10.5 MB
6. PCA - Main Applications.srt	4.0 KB
7. PCA - Image Compression.mp4	262.1 MB
7. PCA - Image Compression.srt	40.3 KB
8. PCA Data Preprocessing.mp4	126.3 MB
8. PCA Data Preprocessing.srt	21.6 KB
9. PCA - Biplot and the Screen Plot.mp4	142.2 MB
9. PCA - Biplot and the Screen Plot.srt	27.0 KB
/2. Data Science & Machine Learning Concepts/
1. Why We Use Python.mp4	14.2 MB
1. Why We Use Python.srt	5.0 KB
2. What is Data Science.mp4	92.3 MB
2. What is Data Science.srt	21.7 KB
3. What is Machine Learning.mp4	87.5 MB
3. What is Machine Learning.srt	23.5 KB
4. Machine Learning Concepts & Algorithms.mp4	81.8 MB
4. Machine Learning Concepts & Algorithms.srt	24.1 KB
5. What is Deep Learning.mp4	81.6 MB
5. What is Deep Learning.srt	16.2 KB
6. Machine Learning vs Deep Learning.mp4	79.6 MB
6. Machine Learning vs Deep Learning.srt	18.3 KB
/20. Data Science Career/
1. Creating A Data Science Resume.mp4	38.9 MB
1. Creating A Data Science Resume.srt	10.8 KB
2. Data Science Cover Letter.mp4	24.1 MB
2. Data Science Cover Letter.srt	6.1 KB
3. How to Contact Recruiters.mp4	25.8 MB
3. How to Contact Recruiters.srt	7.5 KB
4. Getting Started with Freelancing.mp4	31.7 MB
4. Getting Started with Freelancing.srt	7.2 KB
5. Top Freelance Websites.mp4	31.0 MB
5. Top Freelance Websites.srt	8.6 KB
6. Personal Branding.mp4	32.0 MB
6. Personal Branding.srt	6.6 KB
7. Networking Do's and Don'ts.mp4	24.8 MB
7. Networking Do's and Don'ts.srt	6.4 KB
8. Importance of a Website.mp4	16.1 MB
8. Importance of a Website.srt	4.9 KB
/3. Python For Data Science/
1. What is Programming.mp4	19.2 MB
1. What is Programming.srt	9.2 KB
10. Python Conditional Statements.mp4	57.3 MB
10. Python Conditional Statements.srt	18.6 KB
11. Python For Loops and While Loops.mp4	26.8 MB
11. Python For Loops and While Loops.srt	11.0 KB
12. Python Lists.mp4	22.5 MB
12. Python Lists.srt	7.3 KB
13. More about Lists.mp4	63.4 MB
13. More about Lists.srt	19.9 KB
14. Python Tuples.mp4	57.2 MB
14. Python Tuples.srt	15.3 KB
15. Python Dictionaries.mp4	109.2 MB
15. Python Dictionaries.srt	28.4 KB
16. Python Sets.mp4	30.9 MB
16. Python Sets.srt	13.8 KB
17. Compound Data Types & When to use each one.mp4	49.4 MB
17. Compound Data Types & When to use each one.srt	18.4 KB
18. Python Functions.mp4	65.5 MB
18. Python Functions.srt	21.3 KB
19. Object Oriented Programming in Python.mp4	73.7 MB
19. Object Oriented Programming in Python.srt	26.3 KB
2. Why Python for Data Science.mp4	17.1 MB
2. Why Python for Data Science.srt	6.9 KB
2.1 Importing Python Data.pdf	63.0 KB
2.2 Python Basics.pdf	130.8 KB
3. What is Jupyter.mp4	15.3 MB
3. What is Jupyter.srt	6.1 KB
3.1 Jupyter Notebook.pdf	314.5 KB
4. What is Google Colab.mp4	8.7 MB
4. What is Google Colab.srt	5.0 KB
5. Python Variables, Booleans and None.mp4	40.1 MB
5. Python Variables, Booleans and None.srt	15.6 KB
6. Getting Started with Google Colab.mp4	36.8 MB
6. Getting Started with Google Colab.srt	12.7 KB
7. Python Operators.mp4	91.0 MB
7. Python Operators.srt	32.2 KB
8. Python Numbers & Booleans.mp4	26.9 MB
8. Python Numbers & Booleans.srt	9.8 KB
9. Python Strings.mp4	59.0 MB
9. Python Strings.srt	16.5 KB
[CourseClub.Me].url	0.1 KB
[GigaCourse.Com].url	0.0 KB
/4. Statistics for Data Science/
1. Intro To Statistics.mp4	22.3 MB
1. Intro To Statistics.srt	11.4 KB
2. Descriptive Statistics.mp4	22.5 MB
2. Descriptive Statistics.srt	10.3 KB
3. Measure of Variability.mp4	40.1 MB
3. Measure of Variability.srt	18.6 KB
4. Measure of Variability Continued.mp4	36.3 MB
4. Measure of Variability Continued.srt	13.6 KB
5. Measures of Variable Relationship.mp4	24.7 MB
5. Measures of Variable Relationship.srt	11.0 KB
6. Inferential Statistics.mp4	47.2 MB
6. Inferential Statistics.srt	22.6 KB
7. Measure of Asymmetry.mp4	7.1 MB
7. Measure of Asymmetry.srt	2.8 KB
8. Sampling Distribution.mp4	27.7 MB
8. Sampling Distribution.srt	10.5 KB
/5. Probability & Hypothesis Testing/
1. What is Exactly is Probability.mp4	28.5 MB
1. What is Exactly is Probability.srt	6.9 KB
2. Expected Values.mp4	15.4 MB
2. Expected Values.srt	4.2 KB
3. Relative Frequency.mp4	34.3 MB
3. Relative Frequency.srt	8.9 KB
4. Hypothesis Testing Overview.mp4	63.5 MB
4. Hypothesis Testing Overview.srt	14.9 KB
/6. NumPy Data Analysis/
1. Intro NumPy Array Data Types.mp4	36.4 MB
1. Intro NumPy Array Data Types.srt	18.7 KB
1.1 NumPy Basics.pdf	79.0 KB
2. NumPy Arrays.mp4	33.9 MB
2. NumPy Arrays.srt	11.4 KB
3. NumPy Arrays Basics.mp4	41.9 MB
3. NumPy Arrays Basics.srt	17.2 KB
4. NumPy Array Indexing.mp4	36.4 MB
4. NumPy Array Indexing.srt	14.4 KB
5. NumPy Array Computations.mp4	17.8 MB
5. NumPy Array Computations.srt	8.8 KB
6. Broadcasting.mp4	18.7 MB
6. Broadcasting.srt	6.5 KB
/7. Pandas Data Analysis/
1. Introduction to Pandas.mp4	49.1 MB
1. Introduction to Pandas.srt	22.8 KB
1.1 Pandas.pdf	112.8 KB
1.2 Pandas Basics.pdf	78.9 KB
2. Introduction to Pandas Continued.mp4	74.5 MB
2. Introduction to Pandas Continued.srt	27.5 KB
/8. Python Data Visualization/
1. Data Visualization Overview.mp4	76.6 MB
1. Data Visualization Overview.srt	37.7 KB
2. Different Data Visualization Libraries in Python.mp4	16.7 MB
2. Different Data Visualization Libraries in Python.srt	9.0 KB
3. Python Data Visualization Implementation.mp4	28.8 MB
3. Python Data Visualization Implementation.srt	12.7 KB
/9. Machine Learning/
1. Introduction To Machine Learning.mp4	103.5 MB
1. Introduction To Machine Learning.srt	37.9 KB
1.1 Supervised Learning.pdf	856.8 KB
[CourseClub.Me].url	0.1 KB
[GigaCourse.Com].url	0.0 KB
/
[CourseClub.Me].url	0.1 KB
[GigaCourse.Com].url	0.0 KB
Total files 298