Udemy - Complete Linear Regression Analysis in Python [FCS]

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• [CourseClub.ME].url (0.1 KB)
• [FCS Forum].url (0.1 KB)
• [FreeCourseSite.com].url (0.1 KB)
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• 1. Welcome to the course!.mp4 (16.3 MB)
• 1. Welcome to the course!.srt (3.5 KB)
• 2. Course contents.mp4 (47.8 MB)
• 2. Course contents.srt (9.5 KB)
• 2.1 00_Introduction_01.pdf (801.5 KB)
• 3. Course Resources.html (0.3 KB)
• 4. This is a milestone!.mp4 (20.7 MB)
• 4. This is a milestone!.srt (3.8 KB)

• 1. Installing Python and Anaconda.mp4 (18.6 MB)
• 1. Installing Python and Anaconda.srt (2.5 KB)
• 2. Opening Jupyter Notebook.mp4 (73.1 MB)
• 2. Opening Jupyter Notebook.srt (8.9 KB)
• 3. Introduction to Jupyter.mp4 (51.3 MB)
• 3. Introduction to Jupyter.srt (12.4 KB)
• 4. Arithmetic operators in Python Python Basics.mp4 (15.9 MB)
• 4. Arithmetic operators in Python Python Basics.srt (4.2 KB)
• 5. Strings in Python Python Basics.mp4 (80.6 MB)
• 5. Strings in Python Python Basics.srt (16.9 KB)
• 6. Lists, Tuples and Directories Python Basics.mp4 (73.7 MB)
• 6. Lists, Tuples and Directories Python Basics.srt (17.6 KB)
• 7. Working with Numpy Library of Python.mp4 (54.1 MB)
• 7. Working with Numpy Library of Python.srt (10.9 KB)
• 8. Working with Pandas Library of Python.mp4 (56.5 MB)
• 8. Working with Pandas Library of Python.srt (8.8 KB)
• 8.1 Customer.csv (64.0 KB)
• 9. Working with Seaborn Library of Python.mp4 (48.9 MB)
• 9. Working with Seaborn Library of Python.srt (7.3 KB)

• 1. Types of Data.mp4 (21.8 MB)
• 1. Types of Data.srt (5.0 KB)
• 1.1 01_01_Lecture_TypesOfData.pdf (177.7 KB)
• 2. Types of Statistics.mp4 (10.9 MB)
• 2. Types of Statistics.srt (3.2 KB)
• 2.1 01_02_Lecture_TypesOfStatistics.pdf (171.7 KB)
• 3. Describing data Graphically.mp4 (65.4 MB)
• 3. Describing data Graphically.srt (12.8 KB)
• 3.1 01_03_Lecture_DataSummaryandGraph.pdf (317.9 KB)
• 4. Measures of Centers.mp4 (38.6 MB)
• 4. Measures of Centers.srt (7.9 KB)
• 4.1 01_04_Lecture_Centers.pdf (323.0 KB)
• 5. Practice Exercise 1.html (0.3 KB)
• 5.1 Exercise 1.pdf (553.8 KB)
• 6. Measures of Dispersion.mp4 (22.9 MB)
• 6. Measures of Dispersion.srt (5.2 KB)
• 7. Practice Exercise 2.html (0.3 KB)
• 7.1 Exercise 2.pdf (469.9 KB)

• 1. Introduction to Machine Learning.mp4 (123.9 MB)
• 1. Introduction to Machine Learning.srt (18.6 KB)
• 1.1 Lecture_machineLearning.pdf (991.6 KB)
• 2. Building a Machine Learning Model.mp4 (45.3 MB)
• 2. Building a Machine Learning Model.srt (9.9 KB)
• 2.1 Lecture_machineLearning.pdf (1,001.6 KB)
• 3. Introduction to Machine learning quiz.html (0.2 KB)

• 1. Gathering Business Knowledge.mp4 (25.1 MB)
• 1. Gathering Business Knowledge.srt (4.0 KB)
• 1.1 03_01_PDE_Business_knowledge.pdf (153.9 KB)
• 10. Outlier Treatment in Python.mp4 (86.6 MB)
• 10. Outlier Treatment in Python.srt (12.7 KB)
• 11. Project Exercise 3.html (0.2 KB)
• 12. Missing Value Imputation.mp4 (27.6 MB)
• 12. Missing Value Imputation.srt (4.1 KB)
• 12.1 04_05_PDE_Missing_value.pdf (315.7 KB)
• 13. Missing Value Imputation in Python.mp4 (28.6 MB)
• 13. Missing Value Imputation in Python.srt (4.1 KB)
• 14. Project Exercise 4.html (0.2 KB)
• 15. Seasonality in Data.mp4 (20.9 MB)
• 15. Seasonality in Data.srt (3.8 KB)
• 15.1 04_07_PDE_Seasonality.pdf (364.1 KB)
• 16. Bi-variate analysis and Variable transformation.mp4 (113.7 MB)
• 16. Bi-variate analysis and Variable transformation.srt (18.5 KB)
• 16.1 04_07_Variable_Transformation.pdf (422.8 KB)
• 17. Variable transformation and deletion in Python.mp4 (53.4 MB)
• 17. Variable transformation and deletion in Python.srt (7.5 KB)
• 18. Project Exercise 5.html (0.3 KB)
• 19. Non-usable variables.mp4 (23.9 MB)
• 19. Non-usable variables.srt (5.7 KB)
• 19.1 04_08_PDE_Non_Usable_var.pdf (138.3 KB)
• 2. Data Exploration.mp4 (23.4 MB)
• 2. Data Exploration.srt (3.7 KB)
• 2.1 03_02_PDE_Data_exploration.pdf (322.9 KB)
• 20. Dummy variable creation Handling qualitative data.mp4 (40.6 MB)
• 20. Dummy variable creation Handling qualitative data.srt (5.3 KB)
• 20.1 04_11_Dummy_Var.pdf (163.0 KB)
• 21. Dummy variable creation in Python.mp4 (33.9 MB)
• 21. Dummy variable creation in Python.srt (5.3 KB)
• 22. Project Exercise 6.html (0.2 KB)
• 23. Correlation Analysis.mp4 (81.3 MB)
• 23. Correlation Analysis.srt (11.7 KB)
• 23.1 04_10_Correlation.pdf (266.9 KB)
• 24. Correlation Analysis in Python.mp4 (68.0 MB)
• 24. Correlation Analysis in Python.srt (6.7 KB)
• 25. Project Exercise 7.html (0.3 KB)
• 26. Quiz.html (0.2 KB)
• 3. The Dataset and the Data Dictionary.mp4 (78.6 MB)
• 3. The Dataset and the Data Dictionary.srt (8.1 KB)
• 3.1 03_03_PDE_Raw_Data_Analysis_Uni.pdf (332.0 KB)
• 3.2 House_Price.csv (53.5 KB)
• 4. Importing Data in Python.mp4 (32.5 MB)
• 4. Importing Data in Python.srt (5.6 KB)
• 4.1 House_Price.csv (53.5 KB)
• 5. Project exercise 1.html (0.4 KB)
• 5.1 Movie_collection_train.csv (43.3 KB)
• 6. Univariate analysis and EDD.mp4 (27.3 MB)
• 6. Univariate analysis and EDD.srt (3.7 KB)
• 6.1 03_04_PDE_Univariate_Analysis_Uni.pdf (333.4 KB)
• 7. EDD in Python.mp4 (75.1 MB)
• 7. EDD in Python.srt (10.4 KB)
• 8. Project Exercise 2.html (0.2 KB)
• 9. Outlier Treatment.mp4 (27.8 MB)
• 9. Outlier Treatment.srt (4.8 KB)
• 9.1 04_06_PDE_Outlier_Treatment.pdf (355.1 KB)

• 1. The Problem Statement.mp4 (10.7 MB)
• 1. The Problem Statement.srt (1.6 KB)
• 1.1 05_01_Intro.pdf (239.3 KB)
• 10. Interpreting results of Categorical variables.mp4 (27.1 MB)
• 10. Interpreting results of Categorical variables.srt (5.3 KB)
• 10.1 05_06_Cat_var.pdf (155.5 KB)
• 11. Multiple Linear Regression in Python.mp4 (88.1 MB)
• 11. Multiple Linear Regression in Python.srt (12.8 KB)
• 12. Quiz.html (0.2 KB)
• 13. Project Exercise 9.html (0.3 KB)
• 14. Test-train split.mp4 (49.1 MB)
• 14. Test-train split.srt (10.3 KB)
• 14.1 05_12_Test_Train.pdf (238.8 KB)
• 15. Bias Variance trade-off.mp4 (29.6 MB)
• 15. Bias Variance trade-off.srt (6.6 KB)
• 15.1 05_13_Bias_Var_tradeoff.pdf (212.4 KB)
• 16. More about test-train split.html (0.5 KB)
• 17. Test train split in Python.mp4 (57.8 MB)
• 17. Test train split in Python.srt (7.8 KB)
• 18. Quiz.html (0.2 KB)
• 19. Linear models other than OLS.mp4 (19.2 MB)
• 19. Linear models other than OLS.srt (4.4 KB)
• 19.1 05_09_Other_lin_model.pdf (156.5 KB)
• 2. Basic Equations and Ordinary Least Squares (OLS) method.mp4 (50.3 MB)
• 2. Basic Equations and Ordinary Least Squares (OLS) method.srt (9.8 KB)
• 2.1 05_02_Simple_lin_reg.pdf (284.8 KB)
• 20. Subset selection techniques.mp4 (87.1 MB)
• 20. Subset selection techniques.srt (12.9 KB)
• 20.1 05_10_Subset_Selection.pdf (208.5 KB)
• 21. Shrinkage methods Ridge and Lasso.mp4 (38.6 MB)
• 21. Shrinkage methods Ridge and Lasso.srt (8.5 KB)
• 21.1 05_11_Shrinkage_methods.pdf (188.1 KB)
• 22. Ridge regression and Lasso in Python.mp4 (156.6 MB)
• 22. Ridge regression and Lasso in Python.srt (18.3 KB)
• 23. Heteroscedasticity.mp4 (17.7 MB)
• 23. Heteroscedasticity.srt (2.8 KB)
• 24. Project Exercise 10.html (0.4 KB)
• 25. Final Project Exercise.html (0.3 KB)
• 25.1 Movie_collection_test.csv (11.7 KB)
• 3. Assessing accuracy of predicted coefficients.mp4 (104.4 MB)
• 3. Assessing accuracy of predicted coefficients.srt (16.1 KB)
• 3.1 05_03_Simple_lin_reg_Accuracy.pdf (332.7 KB)
• 4. Assessing Model Accuracy RSE and R squared.mp4 (49.7 MB)
• 4. Assessing Model Accuracy RSE and R squared.srt (7.8 KB)
• 4.1 05_03_Simple_lin_reg_Accuracy.pdf (332.7 KB)
• 5. Simple Linear Regression in Python.mp4 (78.6 MB)
• 5. Simple Linear Regression in Python.srt (11.7 KB)
• 6. Project Exercise 8.html (0.3 KB)
• 7. Multiple Linear Regression.mp4 (38.9 MB)
• 7. Multiple Linear Regression.srt (5.8 KB)
• 7.1 05_04_Multiple_lin_reg.pdf (219.8 KB)
• 8. The F - statistic.mp4 (64.1 MB)
• 8. The F - statistic.srt (9.1 KB)
• 8.1 05_05_F_stat.pdf (328.5 KB)
• 9. Quiz.html (0.2 KB)

• 1. The final milestone!.mp4 (11.9 MB)
• 1. The final milestone!.srt (1.7 KB)
• 2. Congratulations & About your certificate.html (1.9 KB)