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文档列表

6. Linear Regression/22. Ridge regression and Lasso in Python.mp4 164.2 MB
4. Introduction to Machine Learning/1. Introduction to Machine Learning.mp4 129.9 MB
5. Data Preprocessing/16. Bi-variate analysis and Variable transformation.mp4 119.3 MB
6. Linear Regression/3. Assessing accuracy of predicted coefficients.mp4 109.5 MB
6. Linear Regression/11. Multiple Linear Regression in Python.mp4 92.4 MB
6. Linear Regression/20. Subset selection techniques.mp4 91.4 MB
5. Data Preprocessing/10. Outlier Treatment in Python.mp4 90.8 MB
5. Data Preprocessing/23. Correlation Analysis.mp4 85.3 MB
2. Setting up Python and Jupyter Notebook/5. Strings in Python Python Basics.mp4 84.6 MB
6. Linear Regression/5. Simple Linear Regression in Python.mp4 82.5 MB
5. Data Preprocessing/3. The Dataset and the Data Dictionary.mp4 82.4 MB
5. Data Preprocessing/7. EDD in Python.mp4 78.7 MB
2. Setting up Python and Jupyter Notebook/6. Lists, Tuples and Directories Python Basics.mp4 77.3 MB
2. Setting up Python and Jupyter Notebook/2. Opening Jupyter Notebook.mp4 76.6 MB
5. Data Preprocessing/24. Correlation Analysis in Python.mp4 71.3 MB
3. Basics of Statistics/3. Describing data Graphically.mp4 68.6 MB
6. Linear Regression/8. The F - statistic.mp4 67.2 MB
6. Linear Regression/17. Test train split in Python.mp4 60.6 MB
2. Setting up Python and Jupyter Notebook/8. Working with Pandas Library of Python.mp4 59.2 MB
2. Setting up Python and Jupyter Notebook/7. Working with Numpy Library of Python.mp4 56.8 MB
5. Data Preprocessing/17. Variable transformation and deletion in Python.mp4 56.0 MB
2. Setting up Python and Jupyter Notebook/3. Introduction to Jupyter.mp4 53.8 MB
6. Linear Regression/2. Basic Equations and Ordinary Least Squares (OLS) method.mp4 52.7 MB
6. Linear Regression/4. Assessing Model Accuracy RSE and R squared.mp4 52.1 MB
6. Linear Regression/14. Test-train split.mp4 51.5 MB
2. Setting up Python and Jupyter Notebook/9. Working with Seaborn Library of Python.mp4 51.2 MB
1. Introduction/2. Course contents.mp4 50.2 MB
4. Introduction to Machine Learning/2. Building a Machine Learning Model.mp4 47.5 MB
5. Data Preprocessing/20. Dummy variable creation Handling qualitative data.mp4 42.6 MB
6. Linear Regression/7. Multiple Linear Regression.mp4 40.8 MB
6. Linear Regression/21. Shrinkage methods Ridge and Lasso.mp4 40.5 MB
3. Basics of Statistics/4. Measures of Centers.mp4 40.4 MB
5. Data Preprocessing/21. Dummy variable creation in Python.mp4 35.6 MB
5. Data Preprocessing/4. Importing Data in Python.mp4 34.0 MB
6. Linear Regression/15. Bias Variance trade-off.mp4 31.0 MB
5. Data Preprocessing/13. Missing Value Imputation in Python.mp4 30.0 MB
5. Data Preprocessing/9. Outlier Treatment.mp4 29.1 MB
5. Data Preprocessing/12. Missing Value Imputation.mp4 28.9 MB
5. Data Preprocessing/6. Univariate analysis and EDD.mp4 28.6 MB
6. Linear Regression/10. Interpreting results of Categorical variables.mp4 28.4 MB
5. Data Preprocessing/1. Gathering Business Knowledge.mp4 26.3 MB
5. Data Preprocessing/19. Non-usable variables.mp4 25.1 MB
5. Data Preprocessing/2. Data Exploration.mp4 24.5 MB
3. Basics of Statistics/6. Measures of Dispersion.mp4 24.0 MB
3. Basics of Statistics/1. Types of Data.mp4 22.8 MB
5. Data Preprocessing/15. Seasonality in Data.mp4 21.9 MB
1. Introduction/4. This is a milestone!.mp4 21.7 MB
6. Linear Regression/19. Linear models other than OLS.mp4 20.1 MB
2. Setting up Python and Jupyter Notebook/1. Installing Python and Anaconda.mp4 19.5 MB
6. Linear Regression/23. Heteroscedasticity.mp4 18.6 MB
1. Introduction/1. Welcome to the course!.mp4 17.1 MB
2. Setting up Python and Jupyter Notebook/4. Arithmetic operators in Python Python Basics.mp4 16.7 MB
7. Bonus Section/1. The final milestone!.mp4 12.5 MB
3. Basics of Statistics/2. Types of Statistics.mp4 11.5 MB
6. Linear Regression/1. The Problem Statement.mp4 11.2 MB
4. Introduction to Machine Learning/2.1 Lecture_machineLearning.pdf 1.0 MB
4. Introduction to Machine Learning/1.1 Lecture_machineLearning.pdf 1.0 MB
1. Introduction/2.1 00_Introduction_01.pdf 820.7 kB
3. Basics of Statistics/5.1 Exercise 1.pdf 567.1 kB
3. Basics of Statistics/7.1 Exercise 2.pdf 481.2 kB
5. Data Preprocessing/16.1 04_07_Variable_Transformation.pdf 433.0 kB
5. Data Preprocessing/15.1 04_07_PDE_Seasonality.pdf 372.8 kB
5. Data Preprocessing/9.1 04_06_PDE_Outlier_Treatment.pdf 363.7 kB
5. Data Preprocessing/6.1 03_04_PDE_Univariate_Analysis_Uni.pdf 341.4 kB
6. Linear Regression/3.1 05_03_Simple_lin_reg_Accuracy.pdf 340.7 kB
6. Linear Regression/4.1 05_03_Simple_lin_reg_Accuracy.pdf 340.7 kB
5. Data Preprocessing/3.1 03_03_PDE_Raw_Data_Analysis_Uni.pdf 339.9 kB
6. Linear Regression/8.1 05_05_F_stat.pdf 336.4 kB
3. Basics of Statistics/4.1 01_04_Lecture_Centers.pdf 330.7 kB
5. Data Preprocessing/2.1 03_02_PDE_Data_exploration.pdf 330.7 kB
3. Basics of Statistics/3.1 01_03_Lecture_DataSummaryandGraph.pdf 325.5 kB
5. Data Preprocessing/12.1 04_05_PDE_Missing_value.pdf 323.3 kB
6. Linear Regression/2.1 05_02_Simple_lin_reg.pdf 291.6 kB
5. Data Preprocessing/23.1 04_10_Correlation.pdf 273.3 kB
6. Linear Regression/1.1 05_01_Intro.pdf 245.1 kB
6. Linear Regression/14.1 05_12_Test_Train.pdf 244.5 kB
6. Linear Regression/7.1 05_04_Multiple_lin_reg.pdf 225.1 kB
6. Linear Regression/15.1 05_13_Bias_Var_tradeoff.pdf 217.5 kB
6. Linear Regression/20.1 05_10_Subset_Selection.pdf 213.5 kB
6. Linear Regression/21.1 05_11_Shrinkage_methods.pdf 192.6 kB
3. Basics of Statistics/1.1 01_01_Lecture_TypesOfData.pdf 182.0 kB
3. Basics of Statistics/2.1 01_02_Lecture_TypesOfStatistics.pdf 175.9 kB
5. Data Preprocessing/20.1 04_11_Dummy_Var.pdf 166.9 kB
6. Linear Regression/19.1 05_09_Other_lin_model.pdf 160.3 kB
6. Linear Regression/10.1 05_06_Cat_var.pdf 159.2 kB
5. Data Preprocessing/1.1 03_01_PDE_Business_knowledge.pdf 157.6 kB
5. Data Preprocessing/19.1 04_08_PDE_Non_Usable_var.pdf 141.7 kB
2. Setting up Python and Jupyter Notebook/8.1 Customer.csv 65.6 kB
5. Data Preprocessing/3.2 House_Price.csv 54.8 kB
5. Data Preprocessing/4.1 House_Price.csv 54.8 kB
5. Data Preprocessing/5.1 Movie_collection_train.csv 44.4 kB
4. Introduction to Machine Learning/1. Introduction to Machine Learning.srt 19.0 kB
5. Data Preprocessing/16. Bi-variate analysis and Variable transformation.srt 18.9 kB
6. Linear Regression/22. Ridge regression and Lasso in Python.srt 18.8 kB
2. Setting up Python and Jupyter Notebook/6. Lists, Tuples and Directories Python Basics.srt 18.1 kB
2. Setting up Python and Jupyter Notebook/5. Strings in Python Python Basics.srt 17.4 kB
6. Linear Regression/3. Assessing accuracy of predicted coefficients.srt 16.5 kB
6. Linear Regression/20. Subset selection techniques.srt 13.2 kB
6. Linear Regression/11. Multiple Linear Regression in Python.srt 13.1 kB
3. Basics of Statistics/3. Describing data Graphically.srt 13.1 kB
5. Data Preprocessing/10. Outlier Treatment in Python.srt 13.0 kB
2. Setting up Python and Jupyter Notebook/3. Introduction to Jupyter.srt 12.7 kB
6. Linear Regression/25.1 Movie_collection_test.csv 12.0 kB
5. Data Preprocessing/23. Correlation Analysis.srt 12.0 kB
6. Linear Regression/5. Simple Linear Regression in Python.srt 12.0 kB
2. Setting up Python and Jupyter Notebook/7. Working with Numpy Library of Python.srt 11.1 kB
5. Data Preprocessing/7. EDD in Python.srt 10.6 kB
6. Linear Regression/14. Test-train split.srt 10.6 kB
4. Introduction to Machine Learning/2. Building a Machine Learning Model.srt 10.1 kB
6. Linear Regression/2. Basic Equations and Ordinary Least Squares (OLS) method.srt 10.0 kB
1. Introduction/2. Course contents.srt 9.7 kB
6. Linear Regression/8. The F - statistic.srt 9.3 kB
2. Setting up Python and Jupyter Notebook/2. Opening Jupyter Notebook.srt 9.1 kB
2. Setting up Python and Jupyter Notebook/8. Working with Pandas Library of Python.srt 9.0 kB
6. Linear Regression/21. Shrinkage methods Ridge and Lasso.srt 8.7 kB
5. Data Preprocessing/3. The Dataset and the Data Dictionary.srt 8.3 kB
3. Basics of Statistics/4. Measures of Centers.srt 8.1 kB
6. Linear Regression/4. Assessing Model Accuracy RSE and R squared.srt 8.0 kB
6. Linear Regression/17. Test train split in Python.srt 8.0 kB
5. Data Preprocessing/17. Variable transformation and deletion in Python.srt 7.7 kB
2. Setting up Python and Jupyter Notebook/9. Working with Seaborn Library of Python.srt 7.5 kB
5. Data Preprocessing/24. Correlation Analysis in Python.srt 6.9 kB
6. Linear Regression/15. Bias Variance trade-off.srt 6.7 kB
6. Linear Regression/7. Multiple Linear Regression.srt 6.0 kB
5. Data Preprocessing/19. Non-usable variables.srt 5.8 kB
5. Data Preprocessing/4. Importing Data in Python.srt 5.8 kB
5. Data Preprocessing/20. Dummy variable creation Handling qualitative data.srt 5.5 kB
5. Data Preprocessing/21. Dummy variable creation in Python.srt 5.5 kB
6. Linear Regression/10. Interpreting results of Categorical variables.srt 5.5 kB
3. Basics of Statistics/6. Measures of Dispersion.srt 5.4 kB
3. Basics of Statistics/1. Types of Data.srt 5.2 kB
5. Data Preprocessing/9. Outlier Treatment.srt 4.9 kB
6. Linear Regression/19. Linear models other than OLS.srt 4.5 kB
2. Setting up Python and Jupyter Notebook/4. Arithmetic operators in Python Python Basics.srt 4.3 kB
5. Data Preprocessing/13. Missing Value Imputation in Python.srt 4.2 kB
5. Data Preprocessing/12. Missing Value Imputation.srt 4.2 kB
5. Data Preprocessing/1. Gathering Business Knowledge.srt 4.1 kB
5. Data Preprocessing/15. Seasonality in Data.srt 3.9 kB
1. Introduction/4. This is a milestone!.srt 3.9 kB
5. Data Preprocessing/6. Univariate analysis and EDD.srt 3.8 kB
5. Data Preprocessing/2. Data Exploration.srt 3.8 kB
1. Introduction/1. Welcome to the course!.srt 3.6 kB
3. Basics of Statistics/2. Types of Statistics.srt 3.2 kB
6. Linear Regression/23. Heteroscedasticity.srt 2.8 kB
2. Setting up Python and Jupyter Notebook/1. Installing Python and Anaconda.srt 2.6 kB
7. Bonus Section/2. Congratulations & About your certificate.html 1.9 kB
7. Bonus Section/1. The final milestone!.srt 1.8 kB
6. Linear Regression/1. The Problem Statement.srt 1.7 kB
6. Linear Regression/16. More about test-train split.html 559 Bytes
5. Data Preprocessing/5. Project exercise 1.html 431 Bytes
6. Linear Regression/24. Project Exercise 10.html 424 Bytes
3. Basics of Statistics/5. Practice Exercise 1.html 357 Bytes
1. Introduction/3. Course Resources.html 336 Bytes
6. Linear Regression/13. Project Exercise 9.html 327 Bytes
6. Linear Regression/6. Project Exercise 8.html 322 Bytes
6. Linear Regression/25. Final Project Exercise.html 301 Bytes
3. Basics of Statistics/7. Practice Exercise 2.html 300 Bytes
5. Data Preprocessing/25. Project Exercise 7.html 288 Bytes
5. Data Preprocessing/18. Project Exercise 5.html 285 Bytes
5. Data Preprocessing/14. Project Exercise 4.html 238 Bytes
5. Data Preprocessing/11. Project Exercise 3.html 233 Bytes
4. Introduction to Machine Learning/3. Introduction to Machine learning quiz.html 210 Bytes
5. Data Preprocessing/26. Quiz.html 210 Bytes
6. Linear Regression/12. Quiz.html 210 Bytes
6. Linear Regression/18. Quiz.html 210 Bytes
6. Linear Regression/9. Quiz.html 210 Bytes
5. Data Preprocessing/22. Project Exercise 6.html 202 Bytes
5. Data Preprocessing/8. Project Exercise 2.html 177 Bytes
0. Websites you may like/[FCS Forum].url 133 Bytes
0. Websites you may like/[FreeCourseSite.com].url 127 Bytes
0. Websites you may like/[CourseClub.ME].url 122 Bytes
0. Websites you may like/[GigaCourse.Com].url 49 Bytes

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