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| [CourseClub.Me].url |
122б |
| [CourseClub.Me].url |
122б |
| [CourseClub.Me].url |
122б |
| [CourseClub.Me].url |
122б |
| [CourseClub.ME].url |
122б |
| [GigaCourse.Com].url |
49б |
| [GigaCourse.Com].url |
49б |
| [GigaCourse.Com].url |
49б |
| [GigaCourse.Com].url |
49б |
| [GigaCourse.Com].url |
49б |
| 1. Advance Programming in Python.mp4 |
359.55Мб |
| 1. Advance Programming in Python.srt |
72.86Кб |
| 1. Big Data.mp4 |
84.59Мб |
| 1. Big Data.srt |
14.62Кб |
| 1. Data Analysis using R.mp4 |
19.78Мб |
| 1. Data Analysis using R.srt |
4.29Кб |
| 1. EDA.mp4 |
27.40Мб |
| 1. EDA.srt |
9.79Кб |
| 1. Getting Started with Data Science.mp4 |
71.82Мб |
| 1. Getting Started with Data Science.srt |
13.88Кб |
| 1. Introduction Machine Learning.mp4 |
81.41Мб |
| 1. Introduction Machine Learning.srt |
19.57Кб |
| 1. Let's Start with Statistics.mp4 |
128.91Мб |
| 1. Let's Start with Statistics.srt |
13.25Кб |
| 1. Linear Regression.mp4 |
150.10Мб |
| 1. Linear Regression.srt |
37.20Кб |
| 1. Project Part 1 Let's get our system ready.mp4 |
112.64Мб |
| 1. Project Part 1 Let's get our system ready.srt |
18.44Кб |
| 1. Python for Data Science.mp4 |
52.23Мб |
| 1. Python for Data Science.srt |
5.02Кб |
| 10. Conversion of Data Types in Python.mp4 |
54.20Мб |
| 10. Conversion of Data Types in Python.srt |
7.42Кб |
| 10. Random Variables.mp4 |
57.21Мб |
| 10. Random Variables.srt |
6.04Кб |
| 10. Working on Titanic Data Set.mp4 |
84.75Мб |
| 10. Working on Titanic Data Set.srt |
13.68Кб |
| 11. Normal Probability Distribution.mp4 |
104.21Мб |
| 11. Normal Probability Distribution.srt |
11.28Кб |
| 11. Python IO functions.mp4 |
14.23Мб |
| 11. Python IO functions.srt |
1.70Кб |
| 11. Random Forest.mp4 |
26.11Мб |
| 11. Random Forest.srt |
5.88Кб |
| 12. Central Limit Theorem.mp4 |
49.37Мб |
| 12. Central Limit Theorem.srt |
4.70Кб |
| 12. Output Formatting.mp4 |
75.61Мб |
| 12. Output Formatting.srt |
6.27Кб |
| 12. Types of Random Forest.mp4 |
3.76Мб |
| 12. Types of Random Forest.srt |
1.44Кб |
| 13. Hypothesis Testing for Decision Making.mp4 |
83.86Мб |
| 13. Hypothesis Testing for Decision Making.srt |
8.88Кб |
| 13. User Input in Python.mp4 |
32.47Мб |
| 13. User Input in Python.srt |
2.50Кб |
| 13. Why Random Forest.mp4 |
9.53Мб |
| 13. Why Random Forest.srt |
2.48Кб |
| 14. Application of Random Forest.mp4 |
17.99Мб |
| 14. Application of Random Forest.srt |
3.29Кб |
| 14. Operators in Python.mp4 |
120.69Мб |
| 14. Operators in Python.srt |
22.66Кб |
| 15. Control Flow in Python.mp4 |
273.50Мб |
| 15. Control Flow in Python.srt |
54.46Кб |
| 15. Random Forest Implementation on Titanic Data Set.mp4 |
73.60Мб |
| 15. Random Forest Implementation on Titanic Data Set.srt |
12.33Кб |
| 16. Functions in Python.mp4 |
117.24Мб |
| 16. Functions in Python.srt |
20.27Кб |
| 16. Model Evaluation Technique.mp4 |
31.14Мб |
| 16. Model Evaluation Technique.srt |
7.89Кб |
| 17. Concept of R-Squared.mp4 |
26.84Мб |
| 17. Concept of R-Squared.srt |
5.73Кб |
| 17. Types of Functions in Python.mp4 |
228.92Мб |
| 17. Types of Functions in Python.srt |
33.37Кб |
| 18. Argument in a Function.mp4 |
88.29Мб |
| 18. Argument in a Function.srt |
12.05Кб |
| 18. Linear Regression.mp4 |
76.20Мб |
| 18. Linear Regression.srt |
11.51Кб |
| 19. Classification.mp4 |
21.67Мб |
| 19. Classification.srt |
5.76Кб |
| 19. Recursive Functions in Python.mp4 |
78.23Мб |
| 19. Recursive Functions in Python.srt |
12.07Кб |
| 2. Advance Programming in Python Part 2.mp4 |
599.89Мб |
| 2. Advance Programming in Python Part 2.srt |
121.46Кб |
| 2. Data Analysis using R part 2.mp4 |
22.75Мб |
| 2. Data Analysis using R part 2.srt |
4.77Кб |
| 2. Data Quality Issues.mp4 |
62.75Мб |
| 2. Data Quality Issues.srt |
5.98Кб |
| 2. EDA on Mc'donalds Data Set.mp4 |
689.79Мб |
| 2. EDA on Mc'donalds Data Set.srt |
111.97Кб |
| 2. How to use Linear Regression.mp4 |
303.56Мб |
| 2. How to use Linear Regression.srt |
56.83Кб |
| 2. Intro to Hadoop.mp4 |
57.96Мб |
| 2. Intro to Hadoop.srt |
10.50Кб |
| 2. Project part 2.mp4 |
57.63Мб |
| 2. Project part 2.srt |
10.36Кб |
| 2. Python Installation - Google Collab.mp4 |
36.01Мб |
| 2. Python Installation - Google Collab.srt |
7.76Кб |
| 2. Unsupervised Learning.mp4 |
29.34Мб |
| 2. Unsupervised Learning.srt |
6.70Кб |
| 20. Confusion Matrix.mp4 |
37.17Мб |
| 20. Confusion Matrix.srt |
8.64Кб |
| 20. Lambda or Anonymous Functions in Python.mp4 |
47.04Мб |
| 20. Lambda or Anonymous Functions in Python.srt |
6.79Кб |
| 21. Recall Sensitivity True Rate of Positive.mp4 |
22.86Мб |
| 21. Recall Sensitivity True Rate of Positive.srt |
5.24Кб |
| 22. FB score.mp4 |
36.24Мб |
| 22. FB score.srt |
11.07Кб |
| 23. AUC ROC curve.mp4 |
36.48Мб |
| 23. AUC ROC curve.srt |
8.45Кб |
| 24. Model Evaluation recall Curve.mp4 |
90.30Мб |
| 24. Model Evaluation recall Curve.srt |
15.25Кб |
| 3. All about R Language.mp4 |
58.24Мб |
| 3. All about R Language.srt |
11.78Кб |
| 3. Data Visualisations.mp4 |
263.61Мб |
| 3. Data Visualisations.srt |
45.44Кб |
| 3. Exploratory Data Analysis.mp4 |
438.81Мб |
| 3. Exploratory Data Analysis.srt |
77.99Кб |
| 3. Intro to Tableu.mp4 |
56.97Мб |
| 3. Intro to Tableu.srt |
12.50Кб |
| 3. Logistic Regression.mp4 |
156.33Мб |
| 3. Logistic Regression.srt |
40.02Кб |
| 3. Project Part 3.mp4 |
129.40Мб |
| 3. Project Part 3.srt |
24.07Кб |
| 3. Python Basics.mp4 |
20.12Мб |
| 3. Python Basics.srt |
3.39Кб |
| 3. Reinforement Learning.mp4 |
43.08Мб |
| 3. Reinforement Learning.srt |
8.95Кб |
| 3. Types of Statistics.mp4 |
91.56Мб |
| 3. Types of Statistics.srt |
9.44Кб |
| 4. Bivariate Plotting.mp4 |
148.84Мб |
| 4. Bivariate Plotting.srt |
36.96Кб |
| 4. Identifiers in Python.mp4 |
35.58Мб |
| 4. Identifiers in Python.srt |
4.29Кб |
| 4. Intro to Business Analytics.mp4 |
53.86Мб |
| 4. Intro to Business Analytics.srt |
11.95Кб |
| 4. Logistic Regression on Titanic Data Set.mp4 |
141.05Мб |
| 4. Logistic Regression on Titanic Data Set.srt |
22.32Кб |
| 4. Measures of Spread.mp4 |
148.93Мб |
| 4. Measures of Spread.srt |
12.06Кб |
| 4. Project part 4.mp4 |
113.85Мб |
| 4. Project part 4.srt |
21.68Кб |
| 5. Comments in Python.mp4 |
42.40Мб |
| 5. Comments in Python.srt |
6.28Кб |
| 5. Decision Tree.mp4 |
27.03Мб |
| 5. Decision Tree.srt |
6.96Кб |
| 5. Measures of Shapes.mp4 |
57.64Мб |
| 5. Measures of Shapes.srt |
6.67Кб |
| 5. Multivariate Plotting.mp4 |
336.46Мб |
| 5. Multivariate Plotting.srt |
61.49Кб |
| 5. Project Let's Finalise it.mp4 |
119.42Мб |
| 5. Project Let's Finalise it.srt |
21.62Кб |
| 6. Algorithms used in Decision Treee.mp4 |
86.75Мб |
| 6. Algorithms used in Decision Treee.srt |
24.05Кб |
| 6. Plots Visualisation.mp4 |
87.48Мб |
| 6. Plots Visualisation.srt |
9.56Кб |
| 6. Python Indentation.mp4 |
38.33Мб |
| 6. Python Indentation.srt |
6.26Кб |
| 7. Gini Index.mp4 |
39.13Мб |
| 7. Gini Index.srt |
11.84Кб |
| 7. Inferential Statistics.mp4 |
45.98Мб |
| 7. Inferential Statistics.srt |
5.28Кб |
| 7. Python Statements.mp4 |
17.82Мб |
| 7. Python Statements.srt |
4.08Кб |
| 8. Issues with Decision Tree.mp4 |
36.70Мб |
| 8. Issues with Decision Tree.srt |
8.54Кб |
| 8. Probability.mp4 |
179.78Мб |
| 8. Probability.srt |
13.45Кб |
| 8. Variables in Python.mp4 |
43.55Мб |
| 8. Variables in Python.srt |
6.36Кб |
| 9. Applications of Decision Tree.mp4 |
13.05Мб |
| 9. Applications of Decision Tree.srt |
2.93Кб |
| 9. Conditional Probability.mp4 |
26.45Мб |
| 9. Conditional Probability.srt |
2.97Кб |
| 9. Data Types & Related Stuffs in Python.mp4 |
203.26Мб |
| 9. Data Types & Related Stuffs in Python.srt |
32.66Кб |