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种子名称： [FreeCourseSite.com] Udemy - 2021 Python for Machine Learning & Data Science Masterclass
文件类型： 视频
文件数目： 103个文件
文件大小： 6.35 GB
收录时间： 2021-2-19 14:06
已经下载： 3次
资源热度： 171
最近下载： 2024-12-19 20:23

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[FreeCourseSite.com] Udemy - 2021 Python for Machine Learning & Data Science Masterclass.torrent

1. Introduction to Course/2. COURSE OVERVIEW LECTURE - PLEASE DO NOT SKIP!.mp424.55MB

1. Introduction to Course/3. Anaconda Python and Jupyter Install and Setup.mp498.75MB

1. Introduction to Course/4. Environment Setup.mp449.32MB

10. Linear Regression/1. Introduction to Linear Regression Section.mp48.87MB

10. Linear Regression/10. Linear Regression - Residual Plots.mp459.52MB

10. Linear Regression/11. Linear Regression - Model Deployment and Coefficient Interpretation.mp488.19MB

10. Linear Regression/12. Polynomial Regression - Theory and Motivation.mp444.47MB

10. Linear Regression/13. Polynomial Regression - Creating Polynomial Features.mp452.62MB

10. Linear Regression/14. Polynomial Regression - Training and Evaluation.mp448.86MB

10. Linear Regression/15. Bias Variance Trade-Off.mp443.04MB

10. Linear Regression/16. Polynomial Regression - Choosing Degree of Polynomial.mp472.93MB

10. Linear Regression/17. Polynomial Regression - Model Deployment.mp428.94MB

10. Linear Regression/18. Regularization Overview.mp433.34MB

10. Linear Regression/19. Feature Scaling.mp453.97MB

10. Linear Regression/2. Linear Regression - Algorithm History.mp454.71MB

10. Linear Regression/20. Introduction to Cross Validation.mp462.59MB

10. Linear Regression/21. Regularization Data Setup.mp434.45MB

10. Linear Regression/22. L2 Regularization - Ridge Regression Theory.mp461.09MB

10. Linear Regression/23. L2 Regularization - Ridge Regression - Python Implementation.mp496.42MB

10. Linear Regression/24. L1 Regularization - Lasso Regression - Background and Implementation.mp4100MB

10. Linear Regression/25. L1 and L2 Regularization - Elastic Net.mp493.41MB

10. Linear Regression/26. Linear Regression Project - Data Overview.mp439.07MB

10. Linear Regression/3. Linear Regression - Understanding Ordinary Least Squares.mp486.26MB

10. Linear Regression/4. Linear Regression - Cost Functions.mp436.02MB

10. Linear Regression/5. Linear Regression - Gradient Descent.mp465.04MB

10. Linear Regression/6. Python coding Simple Linear Regression.mp491.92MB

10. Linear Regression/7. Overview of Scikit-Learn and Python.mp445.61MB

10. Linear Regression/8. Linear Regression - Scikit-Learn Train Test Split.mp482.93MB

10. Linear Regression/9. Linear Regression - Scikit-Learn Performance Evaluation - Regression.mp473.64MB

2. OPTIONAL Python Crash Course/2. Python Crash Course - Part One.mp429.52MB

2. OPTIONAL Python Crash Course/3. Python Crash Course - Part Two.mp422.25MB

2. OPTIONAL Python Crash Course/4. Python Crash Course - Part Three.mp423.17MB

2. OPTIONAL Python Crash Course/5. Python Crash Course - Exercise Questions.mp45MB

2. OPTIONAL Python Crash Course/6. Python Crash Course - Exercise Solutions.mp425.1MB

3. Machine Learning Pathway Overview/1. Machine Learning Pathway.mp440.55MB

4. NumPy/1. Introduction to NumPy.mp411.28MB

4. NumPy/2. NumPy Arrays.mp4109.63MB

4. NumPy/4. NumPy Indexing and Selection.mp446.35MB

4. NumPy/5. NumPy Operations.mp448.59MB

4. NumPy/6. NumPy Exercises.mp411.52MB

4. NumPy/7. Numpy Exercises - Solutions.mp448.56MB

5. Pandas/1. Introduction to Pandas.mp421.01MB

5. Pandas/10. Pandas - Useful Methods - Apply on Multiple Columns.mp498.55MB

5. Pandas/11. Pandas - Useful Methods - Statistical Information and Sorting.mp485.65MB

5. Pandas/12. Missing Data - Overview.mp453.18MB

5. Pandas/13. Missing Data - Pandas Operations.mp497.86MB

5. Pandas/14. GroupBy Operations - Part One.mp493.11MB

5. Pandas/15. GroupBy Operations - Part Two - MultiIndex.mp4105.86MB

5. Pandas/16. Combining DataFrames - Concatenation.mp450.51MB

5. Pandas/17. Combining DataFrames - Inner Merge.mp453.61MB

5. Pandas/18. Combining DataFrames - Left and Right Merge.mp427.9MB

5. Pandas/19. Combining DataFrames - Outer Merge.mp439.89MB

5. Pandas/2. Series - Part One.mp438.48MB

5. Pandas/20. Pandas - Text Methods for String Data.mp475.69MB

5. Pandas/21. Pandas - Time Methods for Date and Time Data.mp4101.92MB

5. Pandas/22. Pandas Input and Output - CSV Files.mp449.87MB

5. Pandas/23. Pandas Input and Output - HTML Tables.mp4106.65MB

5. Pandas/24. Pandas Input and Output - Excel Files.mp434.58MB

5. Pandas/25. Pandas Input and Output - SQL Databases.mp4103.19MB

5. Pandas/26. Pandas Pivot Tables.mp4128.74MB

5. Pandas/27. Pandas Project Exercise Overview.mp441.07MB

5. Pandas/28. Pandas Project Exercise Solutions.mp4181.59MB

5. Pandas/3. Series - Part Two.mp445.3MB

5. Pandas/4. DataFrames - Part One - Creating a DataFrame.mp4114.08MB

5. Pandas/5. DataFrames - Part Two - Basic Properties.mp453.91MB

5. Pandas/6. DataFrames - Part Three - Working with Columns.mp489.3MB

5. Pandas/7. DataFrames - Part Four - Working with Rows.mp496.71MB

5. Pandas/8. Pandas - Conditional Filtering.mp490.04MB

5. Pandas/9. Pandas - Useful Methods - Apply on Single Column.mp473.05MB

6. Matplotlib/1. Introduction to Matplotlib.mp421.57MB

6. Matplotlib/10. Matplotlib Exercise Questions Overview.mp450.77MB

6. Matplotlib/11. Matplotlib Exercise Questions - Solutions.mp4123.11MB

6. Matplotlib/2. Matplotlib Basics.mp453.61MB

6. Matplotlib/3. Matplotlib - Understanding the Figure Object.mp425.81MB

6. Matplotlib/4. Matplotlib - Implementing Figures and Axes.mp459.09MB

6. Matplotlib/5. Matplotlib - Figure Parameters.mp423.75MB

6. Matplotlib/6. Matplotlib - Subplots Functionality.mp496.18MB

6. Matplotlib/7. Matplotlib Styling - Legends.mp434.09MB

6. Matplotlib/8. Matplotlib Styling - Colors and Styles.mp481.19MB

6. Matplotlib/9. Advanced Matplotlib Commands (Optional).mp440.44MB

7. Seaborn Data Visualizations/1. Introduction to Seaborn.mp420.01MB

7. Seaborn Data Visualizations/10. Seaborn - Comparison Plots - Coding with Seaborn.mp470.16MB

7. Seaborn Data Visualizations/11. Seaborn Grid Plots.mp491.62MB

7. Seaborn Data Visualizations/12. Seaborn - Matrix Plots.mp471.25MB

7. Seaborn Data Visualizations/13. Seaborn Plot Exercises Overview.mp449.91MB

7. Seaborn Data Visualizations/14. Seaborn Plot Exercises Solutions.mp4110.6MB

7. Seaborn Data Visualizations/2. Scatterplots with Seaborn.mp4128.61MB

7. Seaborn Data Visualizations/3. Distribution Plots - Part One - Understanding Plot Types.mp432.05MB

7. Seaborn Data Visualizations/4. Distribution Plots - Part Two - Coding with Seaborn.mp477.74MB

7. Seaborn Data Visualizations/5. Categorical Plots - Statistics within Categories - Understanding Plot Types.mp421.86MB

7. Seaborn Data Visualizations/6. Categorical Plots - Statistics within Categories - Coding with Seaborn.mp455MB

7. Seaborn Data Visualizations/7. Categorical Plots - Distributions within Categories - Understanding Plot Types.mp461.09MB

7. Seaborn Data Visualizations/8. Categorical Plots - Distributions within Categories - Coding with Seaborn.mp4111.24MB

7. Seaborn Data Visualizations/9. Seaborn - Comparison Plots - Understanding the Plot Types.mp423.35MB

8. Data Analysis and Visualization Capstone Project Exercise/1. Capstone Project Overview.mp493.2MB

8. Data Analysis and Visualization Capstone Project Exercise/2. Capstone Project Solutions - Part One.mp4116.95MB

8. Data Analysis and Visualization Capstone Project Exercise/3. Capstone Project Solutions - Part Two.mp4111.05MB

8. Data Analysis and Visualization Capstone Project Exercise/4. Capstone Project Solutions - Part Three.mp4143.96MB

9. Machine Learning Concepts Overview/1. Introduction to Machine Learning Overview Section.mp429.73MB

9. Machine Learning Concepts Overview/2. Why Machine Learning.mp444.77MB

9. Machine Learning Concepts Overview/3. Types of Machine Learning Algorithms.mp438.68MB

9. Machine Learning Concepts Overview/4. Supervised Machine Learning Process.mp471.41MB

9. Machine Learning Concepts Overview/5. Companion Book - Introduction to Statistical Learning.mp419.29MB