[DesireCourse.Com] Udemy - Machine Learning Basics Building Regression Model in Python

Creation Time	Jan. 30, 2025, 3:21 a.m.
Last Access Time	Oct. 18, 2025, 3:06 p.m.
File Size	2.7 GB
Keywords	Building Basics Python DesireCourse - Udemy Machine Learning in Model Com Regression
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Total Files	158
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6. Linear Regression/18. Ridge regression and Lasso in Python.mp4 156.6 MB
4. Introduction to Machine Learning/1. Introduction to Machine Learning.mp4 123.9 MB
5. Data Preprocessing/16. Bi-variate analysis and Variable transformation.mp4 113.7 MB
6. Linear Regression/3. Assessing accuracy of predicted coefficients.mp4 104.4 MB
6. Linear Regression/10. Multiple Linear Regression in Python.mp4 88.1 MB
6. Linear Regression/16. Subset selection techniques.mp4 87.1 MB
5. Data Preprocessing/10. Outlier Treatment in Python.mp4 86.6 MB
2. Basics of Statistics/3. Describing data Graphically.mp4 82.2 MB
5. Data Preprocessing/23. Correlation Analysis.mp4 81.3 MB
3. Setting up Python and Jupyter Notebook/5. Strings in Python Python Basics.mp4 80.6 MB
6. Linear Regression/5. Simple Linear Regression in Python.vtt 78.6 MB
6. Linear Regression/5. Simple Linear Regression in Python.mp4 78.6 MB
5. Data Preprocessing/3. The Dataset and the Data Dictionary.mp4 78.6 MB
5. Data Preprocessing/7. EDD in Python.mp4 75.1 MB
3. Setting up Python and Jupyter Notebook/6. Lists, Tuples and Directories Python Basics.mp4 73.7 MB
3. Setting up Python and Jupyter Notebook/2. Opening Jupyter Notebook.mp4 73.1 MB
5. Data Preprocessing/24. Correlation Analysis in Python.mp4 68.0 MB
6. Linear Regression/8. The F - statistic.mp4 64.1 MB
6. Linear Regression/14. Test train split in Python.mp4 57.8 MB
3. Setting up Python and Jupyter Notebook/8. Working with Panda Library of Python.mp4 56.5 MB
3. Setting up Python and Jupyter Notebook/7. Working with Numpy Library of Python.mp4 54.1 MB
5. Data Preprocessing/17. Variable transformation and deletion in Python.mp4 53.4 MB
3. Setting up Python and Jupyter Notebook/3. Introduction to Jupyter.mp4 51.3 MB
6. Linear Regression/2. Basic Equations and Ordinary Least Squares (OLS) method.mp4 50.3 MB
6. Linear Regression/4. Assessing Model Accuracy RSE and R squared.mp4 49.7 MB
6. Linear Regression/12. Test-train split.mp4 49.1 MB
3. Setting up Python and Jupyter Notebook/9. Working with Seaborn Library of Python.mp4 48.9 MB
1. Introduction/2. Course contents.mp4 47.8 MB
2. Basics of Statistics/4. Measures of Centers.mp4 45.7 MB
4. Introduction to Machine Learning/2. Building a Machine Learning Model.mp4 45.3 MB
5. Data Preprocessing/20. Dummy variable creation Handling qualitative data.mp4 40.6 MB
6. Linear Regression/7. Multiple Linear Regression.mp4 38.9 MB
6. Linear Regression/17. Shrinkage methods Ridge and Lasso.mp4 38.6 MB
5. Data Preprocessing/21. Dummy variable creation in Python.mp4 33.9 MB
5. Data Preprocessing/4. Importing Data in Python.mp4 32.5 MB
6. Linear Regression/13. Bias Variance trade-off.mp4 29.6 MB
5. Data Preprocessing/13. Missing Value Imputation in Python.mp4 28.6 MB
2. Basics of Statistics/6. Measures of Dispersion.mp4 28.4 MB
5. Data Preprocessing/9. Outlier Treatment.mp4 27.8 MB
5. Data Preprocessing/12. Missing Value Imputation.mp4 27.6 MB
5. Data Preprocessing/6. Univariate analysis and EDD.mp4 27.3 MB
6. Linear Regression/9. Interpreting results of Categorical variables.mp4 27.1 MB
2. Basics of Statistics/1. Types of Data.mp4 25.9 MB
5. Data Preprocessing/1. Gathering Business Knowledge.mp4 25.1 MB
5. Data Preprocessing/19. Non-usable variables.mp4 23.9 MB
5. Data Preprocessing/2. Data Exploration.mp4 23.4 MB
5. Data Preprocessing/15. Seasonality in Data.mp4 20.9 MB
6. Linear Regression/15. Linear models other than OLS.mp4 19.2 MB
3. Setting up Python and Jupyter Notebook/1. Installing Python and Anaconda.mp4 18.6 MB
1. Introduction/1. Welcome to the course!.mp4 16.3 MB
3. Setting up Python and Jupyter Notebook/4. Arithmetic operators in Python Python Basics.mp4 15.9 MB
2. Basics of Statistics/2. Types of Statistics.mp4 13.2 MB
6. Linear Regression/1. The Problem Statement.mp4 10.7 MB
4. Introduction to Machine Learning/1.1 Lecture_machineLearning.pdf.pdf 991.6 KB
4. Introduction to Machine Learning/2.1 Lecture_machineLearning.pdf.pdf 991.6 KB
1. Introduction/2.1 00_Introduction_01.pdf.pdf 791.5 KB
2. Basics of Statistics/5.1 Exercise 1.pdf.pdf 553.8 KB
2. Basics of Statistics/7.1 Exercise 2.pdf.pdf 469.9 KB
5. Data Preprocessing/16.1 04_07_Variable_Transformation.pdf.pdf 422.8 KB
5. Data Preprocessing/15.1 04_07_PDE_Seasonality.pdf.pdf 364.1 KB
5. Data Preprocessing/9.1 04_06_PDE_Outlier_Treatment.pdf.pdf 355.1 KB
5. Data Preprocessing/6.1 03_04_PDE_Univariate_Analysis_Uni.pdf.pdf 333.4 KB
6. Linear Regression/3.1 05_03_Simple_lin_reg_Accuracy.pdf.pdf 332.7 KB
6. Linear Regression/4.1 05_03_Simple_lin_reg_Accuracy.pdf.pdf 332.7 KB
5. Data Preprocessing/3.1 03_03_PDE_Raw_Data_Analysis_Uni.pdf.pdf 332.0 KB
6. Linear Regression/8.1 05_05_F_stat.pdf.pdf 328.5 KB
5. Data Preprocessing/2.1 03_02_PDE_Data_exploration.pdf.pdf 322.9 KB
2. Basics of Statistics/3.1 01_03_Lecture_DataSummaryandGraph.pdf.pdf 317.9 KB
5. Data Preprocessing/12.1 04_05_PDE_Missing_value.pdf.pdf 315.7 KB
2. Basics of Statistics/4.1 01_04_Lecture_Centers.pdf.pdf 313.0 KB
6. Linear Regression/2.1 05_02_Simple_lin_reg.pdf.pdf 284.8 KB
5. Data Preprocessing/23.1 04_10_Correlation.pdf.pdf 256.9 KB
6. Linear Regression/1.1 05_01_Intro.pdf.pdf 239.3 KB
6. Linear Regression/12.1 05_12_Test_Train.pdf.pdf 238.8 KB
6. Linear Regression/7.1 05_04_Multiple_lin_reg.pdf.pdf 219.8 KB
2. Basics of Statistics/6.1 01_05_Lecture_Dispersion.pdf.pdf 210.6 KB
6. Linear Regression/13.1 05_13_Bias_Var_tradeoff.pdf.pdf 202.4 KB
6. Linear Regression/16.1 05_10_Subset_Selection.pdf.pdf 198.5 KB
6. Linear Regression/17.1 05_11_Shrinkage_methods.pdf.pdf 188.1 KB
2. Basics of Statistics/1.1 01_01_Lecture_TypesOfData.pdf.pdf 177.7 KB
2. Basics of Statistics/2.1 01_02_Lecture_TypesOfStatistics.pdf.pdf 171.7 KB
5. Data Preprocessing/20.1 04_11_Dummy_Var.pdf.pdf 163.0 KB
6. Linear Regression/15.1 05_09_Other_lin_model.pdf.pdf 156.5 KB
6. Linear Regression/9.1 05_06_Cat_var.pdf.pdf 155.5 KB
5. Data Preprocessing/1.1 03_01_PDE_Business_knowledge.pdf.pdf 153.9 KB
5. Data Preprocessing/19.1 04_08_PDE_Non_Usable_var.pdf.pdf 138.3 KB
3. Setting up Python and Jupyter Notebook/8.1 Customer.csv.csv 64.0 KB
5. Data Preprocessing/3.2 House_Price.csv.csv 53.5 KB
5. Data Preprocessing/4.1 House_Price.csv.csv 53.5 KB
5. Data Preprocessing/5.1 Movie_collection_train.csv.csv 43.3 KB
6. Linear Regression/18. Ridge regression and Lasso in Python.vtt 16.5 KB
4. Introduction to Machine Learning/1. Introduction to Machine Learning.vtt 16.3 KB
5. Data Preprocessing/16. Bi-variate analysis and Variable transformation.vtt 16.1 KB
3. Setting up Python and Jupyter Notebook/6. Lists, Tuples and Directories Python Basics.vtt 14.6 KB
3. Setting up Python and Jupyter Notebook/5. Strings in Python Python Basics.vtt 14.3 KB
6. Linear Regression/3. Assessing accuracy of predicted coefficients.vtt 14.0 KB
6. Linear Regression/20.1 Movie_collection_test.csv.csv 11.7 KB
2. Basics of Statistics/3. Describing data Graphically.vtt 11.3 KB
6. Linear Regression/16. Subset selection techniques.vtt 11.2 KB
5. Data Preprocessing/10. Outlier Treatment in Python.vtt 11.2 KB
6. Linear Regression/10. Multiple Linear Regression in Python.vtt 10.8 KB
3. Setting up Python and Jupyter Notebook/3. Introduction to Jupyter.vtt 10.8 KB
5. Data Preprocessing/23. Correlation Analysis.vtt 9.7 KB
3. Setting up Python and Jupyter Notebook/7. Working with Numpy Library of Python.vtt 9.1 KB
5. Data Preprocessing/7. EDD in Python.vtt 9.0 KB
6. Linear Regression/12. Test-train split.vtt 9.0 KB
6. Linear Regression/2. Basic Equations and Ordinary Least Squares (OLS) method.vtt 8.7 KB
4. Introduction to Machine Learning/2. Building a Machine Learning Model.vtt 8.6 KB
1. Introduction/2. Course contents.vtt 8.0 KB
3. Setting up Python and Jupyter Notebook/2. Opening Jupyter Notebook.vtt 8.0 KB
6. Linear Regression/8. The F - statistic.vtt 8.0 KB
3. Setting up Python and Jupyter Notebook/8. Working with Panda Library of Python.vtt 7.2 KB
6. Linear Regression/17. Shrinkage methods Ridge and Lasso.vtt 7.2 KB
6. Linear Regression/4. Assessing Model Accuracy RSE and R squared.vtt 7.1 KB
6. Linear Regression/14. Test train split in Python.vtt 7.0 KB
5. Data Preprocessing/3. The Dataset and the Data Dictionary.vtt 6.9 KB
3. Setting up Python and Jupyter Notebook/9. Working with Seaborn Library of Python.vtt 6.5 KB
5. Data Preprocessing/17. Variable transformation and deletion in Python.vtt 6.5 KB
2. Basics of Statistics/4. Measures of Centers.vtt 6.4 KB
5. Data Preprocessing/24. Correlation Analysis in Python.vtt 5.8 KB
6. Linear Regression/13. Bias Variance trade-off.vtt 5.7 KB
6. Linear Regression/7. Multiple Linear Regression.vtt 5.1 KB
5. Data Preprocessing/4. Importing Data in Python.vtt 4.9 KB
5. Data Preprocessing/19. Non-usable variables.vtt 4.8 KB
5. Data Preprocessing/21. Dummy variable creation in Python.vtt 4.8 KB
2. Basics of Statistics/6. Measures of Dispersion.vtt 4.7 KB
6. Linear Regression/9. Interpreting results of Categorical variables.vtt 4.7 KB
2. Basics of Statistics/1. Types of Data.vtt 4.3 KB
5. Data Preprocessing/20. Dummy variable creation Handling qualitative data.vtt 4.3 KB
5. Data Preprocessing/9. Outlier Treatment.vtt 4.0 KB
6. Linear Regression/15. Linear models other than OLS.vtt 3.9 KB
5. Data Preprocessing/12. Missing Value Imputation.vtt 3.6 KB
5. Data Preprocessing/13. Missing Value Imputation in Python.vtt 3.6 KB
3. Setting up Python and Jupyter Notebook/4. Arithmetic operators in Python Python Basics.vtt 3.5 KB
5. Data Preprocessing/1. Gathering Business Knowledge.vtt 3.4 KB
5. Data Preprocessing/15. Seasonality in Data.vtt 3.3 KB
1. Introduction/1. Welcome to the course!.vtt 3.2 KB
5. Data Preprocessing/2. Data Exploration.vtt 3.2 KB
5. Data Preprocessing/6. Univariate analysis and EDD.vtt 3.1 KB
2. Basics of Statistics/2. Types of Statistics.vtt 2.7 KB
3. Setting up Python and Jupyter Notebook/1. Installing Python and Anaconda.vtt 2.2 KB
6. Linear Regression/21. Course Conclusion.html 1.6 KB
6. Linear Regression/1. The Problem Statement.vtt 1.4 KB
5. Data Preprocessing/5. Project exercise 1.html 431 bytes
6. Linear Regression/19. Project Exercise 10.html 424 bytes
2. Basics of Statistics/5. Practice Exercise 1.html 357 bytes
6. Linear Regression/11. Project Exercise 9.html 327 bytes
6. Linear Regression/6. Project Exercise 8.html 322 bytes
6. Linear Regression/20. Final Project Exercise.html 301 bytes
2. 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
5. Data Preprocessing/22. Project Exercise 6.html 202 bytes
5. Data Preprocessing/8. Project Exercise 2.html 177 bytes
4. Introduction to Machine Learning/3. Introduction to Machine learning quiz.html 166 bytes
[DesireCourse.Com].url 51 bytes

[DesireCourse.Com] Udemy - Machine Learning Basics Building Regression Model in Python

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