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文档列表
5. Let's dig deeper/2. EDA on Mc'donalds Data Set.mp4
723.3 MB
4. Advance Python/2. Advance Programming in Python Part 2.mp4
629.0 MB
5. Let's dig deeper/3. Exploratory Data Analysis.mp4
460.1 MB
4. Advance Python/1. Advance Programming in Python.mp4
377.0 MB
4. Advance Python/5. Multivariate Plotting.mp4
352.8 MB
7. Module Seven/2. How to use Linear Regression.mp4
318.3 MB
3. Python for Data Science/15. Control Flow in Python.mp4
286.8 MB
4. Advance Python/3. Data Visualisations.mp4
276.4 MB
3. Python for Data Science/17. Types of Functions in Python.mp4
240.0 MB
3. Python for Data Science/9. Data Types & Related Stuffs in Python.mp4
213.1 MB
2. Basic Maths Required for Data Science/8. Probability.mp4
188.5 MB
7. Module Seven/3. Logistic Regression.mp4
163.9 MB
7. Module Seven/1. Linear Regression.mp4
157.4 MB
2. Basic Maths Required for Data Science/4. Measures of Spread.mp4
156.2 MB
4. Advance Python/4. Bivariate Plotting.mp4
156.1 MB
7. Module Seven/4. Logistic Regression on Titanic Data Set.mp4
147.9 MB
10. Project Telecom Churn Production/3. Project Part 3.mp4
135.7 MB
2. Basic Maths Required for Data Science/1. Let's Start with Statistics.mp4
135.2 MB
3. Python for Data Science/14. Operators in Python.mp4
126.5 MB
10. Project Telecom Churn Production/5. Project Let's Finalise it.mp4
125.2 MB
3. Python for Data Science/16. Functions in Python.mp4
122.9 MB
10. Project Telecom Churn Production/4. Project part 4.mp4
119.4 MB
10. Project Telecom Churn Production/1. Project Part 1 Let's get our system ready.mp4
118.1 MB
2. Basic Maths Required for Data Science/11. Normal Probability Distribution.mp4
109.3 MB
2. Basic Maths Required for Data Science/3. Types of Statistics.mp4
96.0 MB
7. Module Seven/24. Model Evaluation recall Curve.mp4
94.7 MB
3. Python for Data Science/18. Argument in a Function.mp4
92.6 MB
2. Basic Maths Required for Data Science/6. Plots Visualisation.mp4
91.7 MB
7. Module Seven/6. Algorithms used in Decision Treee.mp4
91.0 MB
7. Module Seven/10. Working on Titanic Data Set.mp4
88.9 MB
9. Featured Topics in Java/1. Big Data.mp4
88.7 MB
2. Basic Maths Required for Data Science/13. Hypothesis Testing for Decision Making.mp4
87.9 MB
6. Let's Explore in to Machine Learning/1. Introduction Machine Learning.mp4
85.4 MB
3. Python for Data Science/19. Recursive Functions in Python.mp4
82.0 MB
7. Module Seven/18. Linear Regression.mp4
79.9 MB
3. Python for Data Science/12. Output Formatting.mp4
79.3 MB
7. Module Seven/15. Random Forest Implementation on Titanic Data Set.mp4
77.2 MB
1. Introduction/1. Getting Started with Data Science.mp4
75.3 MB
2. Basic Maths Required for Data Science/2. Data Quality Issues.mp4
65.8 MB
8. Module Eight/3. All about R Language.mp4
61.1 MB
9. Featured Topics in Java/2. Intro to Hadoop.mp4
60.8 MB
2. Basic Maths Required for Data Science/5. Measures of Shapes.mp4
60.4 MB
10. Project Telecom Churn Production/2. Project part 2.mp4
60.4 MB
2. Basic Maths Required for Data Science/10. Random Variables.mp4
60.0 MB
9. Featured Topics in Java/3. Intro to Tableu.mp4
59.7 MB
3. Python for Data Science/10. Conversion of Data Types in Python.mp4
56.8 MB
9. Featured Topics in Java/4. Intro to Business Analytics.mp4
56.5 MB
3. Python for Data Science/1. Python for Data Science.mp4
54.8 MB
2. Basic Maths Required for Data Science/12. Central Limit Theorem.mp4
51.8 MB
3. Python for Data Science/20. Lambda or Anonymous Functions in Python.mp4
49.3 MB
2. Basic Maths Required for Data Science/7. Inferential Statistics.mp4
48.2 MB
3. Python for Data Science/8. Variables in Python.mp4
45.7 MB
6. Let's Explore in to Machine Learning/3. Reinforement Learning.mp4
45.2 MB
3. Python for Data Science/5. Comments in Python.mp4
44.5 MB
7. Module Seven/7. Gini Index.mp4
41.0 MB
3. Python for Data Science/6. Python Indentation.mp4
40.2 MB
7. Module Seven/20. Confusion Matrix.mp4
39.0 MB
7. Module Seven/8. Issues with Decision Tree.mp4
38.5 MB
7. Module Seven/23. AUC ROC curve.mp4
38.3 MB
7. Module Seven/22. FB score.mp4
38.0 MB
3. Python for Data Science/2. Python Installation - Google Collab.mp4
37.8 MB
3. Python for Data Science/4. Identifiers in Python.mp4
37.3 MB
3. Python for Data Science/13. User Input in Python.mp4
34.0 MB
7. Module Seven/16. Model Evaluation Technique.mp4
32.7 MB
6. Let's Explore in to Machine Learning/2. Unsupervised Learning.mp4
30.8 MB
5. Let's dig deeper/1. EDA.mp4
28.7 MB
7. Module Seven/5. Decision Tree.mp4
28.3 MB
7. Module Seven/17. Concept of R-Squared.mp4
28.1 MB
2. Basic Maths Required for Data Science/9. Conditional Probability.mp4
27.7 MB
7. Module Seven/11. Random Forest.mp4
27.4 MB
7. Module Seven/21. Recall Sensitivity True Rate of Positive.mp4
24.0 MB
8. Module Eight/2. Data Analysis using R part 2.mp4
23.8 MB
7. Module Seven/19. Classification.mp4
22.7 MB
3. Python for Data Science/3. Python Basics.mp4
21.1 MB
8. Module Eight/1. Data Analysis using R.mp4
20.7 MB
7. Module Seven/14. Application of Random Forest.mp4
18.9 MB
3. Python for Data Science/7. Python Statements.mp4
18.7 MB
3. Python for Data Science/11. Python IO functions.mp4
14.9 MB
7. Module Seven/9. Applications of Decision Tree.mp4
13.7 MB
7. Module Seven/13. Why Random Forest.mp4
10.0 MB
7. Module Seven/12. Types of Random Forest.mp4
3.9 MB
4. Advance Python/2. Advance Programming in Python Part 2.srt
124.4 kB
5. Let's dig deeper/2. EDA on Mc'donalds Data Set.srt
114.7 kB
5. Let's dig deeper/3. Exploratory Data Analysis.srt
79.9 kB
4. Advance Python/1. Advance Programming in Python.srt
74.6 kB
4. Advance Python/5. Multivariate Plotting.srt
63.0 kB
7. Module Seven/2. How to use Linear Regression.srt
58.2 kB
3. Python for Data Science/15. Control Flow in Python.srt
55.8 kB
4. Advance Python/3. Data Visualisations.srt
46.5 kB
7. Module Seven/3. Logistic Regression.srt
41.0 kB
7. Module Seven/1. Linear Regression.srt
38.1 kB
4. Advance Python/4. Bivariate Plotting.srt
37.8 kB
3. Python for Data Science/17. Types of Functions in Python.srt
34.2 kB
3. Python for Data Science/9. Data Types & Related Stuffs in Python.srt
33.4 kB
10. Project Telecom Churn Production/3. Project Part 3.srt
24.6 kB
7. Module Seven/6. Algorithms used in Decision Treee.srt
24.6 kB
3. Python for Data Science/14. Operators in Python.srt
23.2 kB
7. Module Seven/4. Logistic Regression on Titanic Data Set.srt
22.9 kB
10. Project Telecom Churn Production/4. Project part 4.srt
22.2 kB
10. Project Telecom Churn Production/5. Project Let's Finalise it.srt
22.1 kB
3. Python for Data Science/16. Functions in Python.srt
20.8 kB
6. Let's Explore in to Machine Learning/1. Introduction Machine Learning.srt
20.0 kB
10. Project Telecom Churn Production/1. Project Part 1 Let's get our system ready.srt
18.9 kB
7. Module Seven/24. Model Evaluation recall Curve.srt
15.6 kB
9. Featured Topics in Java/1. Big Data.srt
15.0 kB
1. Introduction/1. Getting Started with Data Science.srt
14.2 kB
7. Module Seven/10. Working on Titanic Data Set.srt
14.0 kB
2. Basic Maths Required for Data Science/8. Probability.srt
13.8 kB
2. Basic Maths Required for Data Science/1. Let's Start with Statistics.srt
13.6 kB
9. Featured Topics in Java/3. Intro to Tableu.srt
12.8 kB
7. Module Seven/15. Random Forest Implementation on Titanic Data Set.srt
12.6 kB
3. Python for Data Science/19. Recursive Functions in Python.srt
12.4 kB
2. Basic Maths Required for Data Science/4. Measures of Spread.srt
12.3 kB
3. Python for Data Science/18. Argument in a Function.srt
12.3 kB
9. Featured Topics in Java/4. Intro to Business Analytics.srt
12.2 kB
7. Module Seven/7. Gini Index.srt
12.1 kB
8. Module Eight/3. All about R Language.srt
12.1 kB
7. Module Seven/18. Linear Regression.srt
11.8 kB
2. Basic Maths Required for Data Science/11. Normal Probability Distribution.srt
11.5 kB
7. Module Seven/22. FB score.srt
11.3 kB
9. Featured Topics in Java/2. Intro to Hadoop.srt
10.8 kB
10. Project Telecom Churn Production/2. Project part 2.srt
10.6 kB
5. Let's dig deeper/1. EDA.srt
10.0 kB
2. Basic Maths Required for Data Science/6. Plots Visualisation.srt
9.8 kB
2. Basic Maths Required for Data Science/3. Types of Statistics.srt
9.7 kB
6. Let's Explore in to Machine Learning/3. Reinforement Learning.srt
9.2 kB
2. Basic Maths Required for Data Science/13. Hypothesis Testing for Decision Making.srt
9.1 kB
7. Module Seven/20. Confusion Matrix.srt
8.8 kB
7. Module Seven/8. Issues with Decision Tree.srt
8.7 kB
7. Module Seven/23. AUC ROC curve.srt
8.7 kB
7. Module Seven/16. Model Evaluation Technique.srt
8.1 kB
3. Python for Data Science/2. Python Installation - Google Collab.srt
7.9 kB
3. Python for Data Science/10. Conversion of Data Types in Python.srt
7.6 kB
7. Module Seven/5. Decision Tree.srt
7.1 kB
3. Python for Data Science/20. Lambda or Anonymous Functions in Python.srt
7.0 kB
6. Let's Explore in to Machine Learning/2. Unsupervised Learning.srt
6.9 kB
2. Basic Maths Required for Data Science/5. Measures of Shapes.srt
6.8 kB
3. Python for Data Science/8. Variables in Python.srt
6.5 kB
3. Python for Data Science/5. Comments in Python.srt
6.4 kB
3. Python for Data Science/12. Output Formatting.srt
6.4 kB
3. Python for Data Science/6. Python Indentation.srt
6.4 kB
2. Basic Maths Required for Data Science/10. Random Variables.srt
6.2 kB
2. Basic Maths Required for Data Science/2. Data Quality Issues.srt
6.1 kB
7. Module Seven/11. Random Forest.srt
6.0 kB
7. Module Seven/19. Classification.srt
5.9 kB
7. Module Seven/17. Concept of R-Squared.srt
5.9 kB
2. Basic Maths Required for Data Science/7. Inferential Statistics.srt
5.4 kB
7. Module Seven/21. Recall Sensitivity True Rate of Positive.srt
5.4 kB
3. Python for Data Science/1. Python for Data Science.srt
5.1 kB
8. Module Eight/2. Data Analysis using R part 2.srt
4.9 kB
2. Basic Maths Required for Data Science/12. Central Limit Theorem.srt
4.8 kB
8. Module Eight/1. Data Analysis using R.srt
4.4 kB
3. Python for Data Science/4. Identifiers in Python.srt
4.4 kB
3. Python for Data Science/7. Python Statements.srt
4.2 kB
3. Python for Data Science/3. Python Basics.srt
3.5 kB
7. Module Seven/14. Application of Random Forest.srt
3.4 kB
2. Basic Maths Required for Data Science/9. Conditional Probability.srt
3.0 kB
7. Module Seven/9. Applications of Decision Tree.srt
3.0 kB
3. Python for Data Science/13. User Input in Python.srt
2.6 kB
7. Module Seven/13. Why Random Forest.srt
2.5 kB
3. Python for Data Science/11. Python IO functions.srt
1.7 kB
7. Module Seven/12. Types of Random Forest.srt
1.5 kB
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0. Websites you may like/[FreeCourseSite.com].url
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0. Websites you may like/[CourseClub.ME].url
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0. Websites you may like/[GigaCourse.Com].url
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