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[FreeCourseSite.com] Udemy - Data Science with Python Complete Course
magnet:?xt=urn:btih:f90ee7a6e53b9efac7a43362a4a21c79b61d0ff4&dn=[FreeCourseSite.com] Udemy - Data Science with Python Complete Course
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f90ee7a6e53b9efac7a43362a4a21c79b61d0ff4
infohash:
81
文件数量
8.08 GB
文件大小
2023-6-11 00:07
创建日期
2024-12-14 23:53
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相关分词
FreeCourseSite
com
Udemy
-
Data
Science
with
Python
Complete
Course
1. Introduction/1. Getting Started with Data Science.mp4 71.82 MB
10. Project Telecom Churn Production/1. Project Part 1 Let's get our system ready.mp4 112.64 MB
10. Project Telecom Churn Production/2. Project part 2.mp4 57.63 MB
10. Project Telecom Churn Production/3. Project Part 3.mp4 129.4 MB
10. Project Telecom Churn Production/4. Project part 4.mp4 113.85 MB
10. Project Telecom Churn Production/5. Project Let's Finalise it.mp4 119.43 MB
2. Basic Maths Required for Data Science/1. Let's Start with Statistics.mp4 128.91 MB
2. Basic Maths Required for Data Science/10. Random Variables.mp4 57.22 MB
2. Basic Maths Required for Data Science/11. Normal Probability Distribution.mp4 104.21 MB
2. Basic Maths Required for Data Science/12. Central Limit Theorem.mp4 49.37 MB
2. Basic Maths Required for Data Science/13. Hypothesis Testing for Decision Making.mp4 83.86 MB
2. Basic Maths Required for Data Science/2. Data Quality Issues.mp4 62.75 MB
2. Basic Maths Required for Data Science/3. Types of Statistics.mp4 91.56 MB
2. Basic Maths Required for Data Science/4. Measures of Spread.mp4 148.93 MB
2. Basic Maths Required for Data Science/5. Measures of Shapes.mp4 57.64 MB
2. Basic Maths Required for Data Science/6. Plots Visualisation.mp4 87.49 MB
2. Basic Maths Required for Data Science/7. Inferential Statistics.mp4 45.98 MB
2. Basic Maths Required for Data Science/8. Probability.mp4 179.78 MB
2. Basic Maths Required for Data Science/9. Conditional Probability.mp4 26.46 MB
3. Python for Data Science/1. Python for Data Science.mp4 52.24 MB
3. Python for Data Science/10. Conversion of Data Types in Python.mp4 54.2 MB
3. Python for Data Science/11. Python IO functions.mp4 14.24 MB
3. Python for Data Science/12. Output Formatting.mp4 75.6 MB
3. Python for Data Science/13. User Input in Python.mp4 32.47 MB
3. Python for Data Science/14. Operators in Python.mp4 120.69 MB
3. Python for Data Science/15. Control Flow in Python.mp4 273.5 MB
3. Python for Data Science/16. Functions in Python.mp4 117.24 MB
3. Python for Data Science/17. Types of Functions in Python.mp4 228.92 MB
3. Python for Data Science/18. Argument in a Function.mp4 88.29 MB
3. Python for Data Science/19. Recursive Functions in Python.mp4 78.22 MB
3. Python for Data Science/2. Python Installation - Google Collab.mp4 36.01 MB
3. Python for Data Science/20. Lambda or Anonymous Functions in Python.mp4 47.04 MB
3. Python for Data Science/3. Python Basics.mp4 20.12 MB
3. Python for Data Science/4. Identifiers in Python.mp4 35.57 MB
3. Python for Data Science/5. Comments in Python.mp4 42.41 MB
3. Python for Data Science/6. Python Indentation.mp4 38.34 MB
3. Python for Data Science/7. Python Statements.mp4 17.82 MB
3. Python for Data Science/8. Variables in Python.mp4 43.55 MB
3. Python for Data Science/9. Data Types & Related Stuffs in Python.mp4 203.27 MB
4. Advance Python/1. Advance Programming in Python.mp4 359.55 MB
4. Advance Python/2. Advance Programming in Python Part 2.mp4 599.88 MB
4. Advance Python/3. Data Visualisations.mp4 263.61 MB
4. Advance Python/4. Bivariate Plotting.mp4 148.84 MB
4. Advance Python/5. Multivariate Plotting.mp4 336.46 MB
5. Let's dig deeper/1. EDA.mp4 27.41 MB
5. Let's dig deeper/2. EDA on Mc'donalds Data Set.mp4 689.8 MB
5. Let's dig deeper/3. Exploratory Data Analysis.mp4 438.81 MB
6. Let's Explore in to Machine Learning/1. Introduction Machine Learning.mp4 81.42 MB
6. Let's Explore in to Machine Learning/2. Unsupervised Learning.mp4 29.34 MB
6. Let's Explore in to Machine Learning/3. Reinforement Learning.mp4 43.08 MB
7. Module Seven/1. Linear Regression.mp4 150.1 MB
7. Module Seven/10. Working on Titanic Data Set.mp4 84.75 MB
7. Module Seven/11. Random Forest.mp4 26.1 MB
7. Module Seven/12. Types of Random Forest.mp4 3.76 MB
7. Module Seven/13. Why Random Forest.mp4 9.53 MB
7. Module Seven/14. Application of Random Forest.mp4 17.99 MB
7. Module Seven/15. Random Forest Implementation on Titanic Data Set.mp4 73.59 MB
7. Module Seven/16. Model Evaluation Technique.mp4 31.14 MB
7. Module Seven/17. Concept of R-Squared.mp4 26.84 MB
7. Module Seven/18. Linear Regression.mp4 76.2 MB
7. Module Seven/19. Classification.mp4 21.68 MB
7. Module Seven/2. How to use Linear Regression.mp4 303.55 MB
7. Module Seven/20. Confusion Matrix.mp4 37.17 MB
7. Module Seven/21. Recall Sensitivity True Rate of Positive.mp4 22.85 MB
7. Module Seven/22. FB score.mp4 36.24 MB
7. Module Seven/23. AUC ROC curve.mp4 36.48 MB
7. Module Seven/24. Model Evaluation recall Curve.mp4 90.3 MB
7. Module Seven/3. Logistic Regression.mp4 156.34 MB
7. Module Seven/4. Logistic Regression on Titanic Data Set.mp4 141.05 MB
7. Module Seven/5. Decision Tree.mp4 27.03 MB
7. Module Seven/6. Algorithms used in Decision Treee.mp4 86.75 MB
7. Module Seven/7. Gini Index.mp4 39.13 MB
7. Module Seven/8. Issues with Decision Tree.mp4 36.7 MB
7. Module Seven/9. Applications of Decision Tree.mp4 13.06 MB
8. Module Eight/1. Data Analysis using R.mp4 19.78 MB
8. Module Eight/2. Data Analysis using R part 2.mp4 22.74 MB
8. Module Eight/3. All about R Language.mp4 58.24 MB
9. Featured Topics in Java/1. Big Data.mp4 84.59 MB
9. Featured Topics in Java/2. Intro to Hadoop.mp4 57.96 MB
9. Featured Topics in Java/3. Intro to Tableu.mp4 56.97 MB
9. Featured Topics in Java/4. Intro to Business Analytics.mp4 53.86 MB
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