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[DesireCourse Com] Udemy - Machine Learning Basics Building a Regression model in R
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Torrent Files List
1. Introduction (Size: 2.76 GB) (Files: 158)
1. Introduction
1. Welcome to the course!.mp4
1. Welcome to the course!.vtt
2. Course contents.mp4
2. Course contents.vtt
2.1 00_Introduction_01.pdf.pdf
2. Basics of Statistics
1. Types of Data.mp4
1. Types of Data.vtt
1.1 01_01_Lecture_TypesOfData.pdf.pdf
2. Types of Statistics.mp4
2. Types of Statistics.vtt
2.1 01_02_Lecture_TypesOfStatistics.pdf.pdf
3. Describing the data graphically.mp4
3. Describing the data graphically.vtt
3.1 01_03_Lecture_DataSummaryandGraph.pdf.pdf
4. Measures of Centers.mp4
4. Measures of Centers.vtt
4.1 01_04_Lecture_Centers.pdf.pdf
5. Practice Exercise 1.html
5.1 Exercise 1.pdf.pdf
6. Measures of Dispersion.mp4
6. Measures of Dispersion.vtt
6.1 01_05_Lecture_Dispersion.pdf.pdf
7. Practice Exercise 2.html
7.1 Exercise 2.pdf.pdf
3. Getting started with R and R studio
1. Installing R and R studio.mp4
1. Installing R and R studio.vtt
2. Basics of R and R studio.mp4
2. Basics of R and R studio.vtt
3. Packages in R.mp4
3. Packages in R.vtt
4. Inputting data part 1 Inbuilt datasets of R.mp4
4. Inputting data part 1 Inbuilt datasets of R.vtt
5. Inputting data part 2 Manual data entry.mp4
5. Inputting data part 2 Manual data entry.vtt
6. Inputting data part 3 Importing from CSV or Text files.mp4
6. Inputting data part 3 Importing from CSV or Text files.vtt
7. Creating Barplots in R.mp4
7. Creating Barplots in R.vtt
8. Creating Histograms in R.mp4
8. Creating Histograms in R.vtt
4. Introduction to Machine Learning
1. Introduction to Machine Learning.mp4
1. Introduction to Machine Learning.vtt
1.1 Lecture_machineLearning.pdf.pdf
2. Building a Machine Learning model.mp4
2. Building a Machine Learning model.vtt
2.1 Lecture_machineLearning.pdf.pdf
3. Introduction to Machine learning quiz.html
5. Data Preprocessing
1. Gathering Business Knowledge.mp4
1. Gathering Business Knowledge.vtt
1.1 03_01_PDE_Business_knowledge.pdf.pdf
10. Outlier Treatment in R.mp4
10. Outlier Treatment in R.vtt
11. Project Exercise 3.html
12. Missing Value imputation.mp4
12. Missing Value imputation.vtt
12.1 04_05_PDE_Missing_value.pdf.pdf
13. Missing Value imputation in R.mp4
13. Missing Value imputation in R.vtt
14. Project Exercise 4.html
15. Seasonality in Data.mp4
15. Seasonality in Data.vtt
15.1 04_07_PDE_Seasonality.pdf.pdf
16. Bi-variate Analysis and Variable Transformation.mp4
16. Bi-variate Analysis and Variable Transformation.vtt
16.1 04_07_Variable_Transformation.pdf.pdf
17. Variable transformation in R.mp4
17. Variable transformation in R.vtt
18. Project Exercise 5.html
19. Non Usable Variables.mp4
19. Non Usable Variables.vtt
19.1 04_08_PDE_Non_Usable_var.pdf.pdf
2. Data Exploration.mp4
2. Data Exploration.vtt
2.1 03_02_PDE_Data_exploration.pdf.pdf
20. Dummy variable creation Handling qualitative data.mp4
20. Dummy variable creation Handling qualitative data.vtt
20.1 04_11_Dummy_Var.pdf.pdf
21. Dummy variable creation in R.mp4
21. Dummy variable creation in R.vtt
22. Project Exercise 6.html
23. Correlation Matrix and cause-effect relationship.mp4
23. Correlation Matrix and cause-effect relationship.vtt
23.1 04_10_Correlation.pdf.pdf
24. Correlation Matrix in R.mp4
24. Correlation Matrix in R.vtt
25. Project Exercise 7.html
3. The Data and the Data Dictionary.mp4
3. The Data and the Data Dictionary.vtt
3.1 House_Price.csv.csv
3.2 03_03_PDE_Raw_Data_Analysis_Uni.pdf.pdf
4. Importing the dataset into R.mp4
4. Importing the dataset into R.vtt
4.1 House_Price.csv.csv
5. Project Exercise 1.html
5.1 Movie_collection_train.csv.csv
6. Univariate Analysis and EDD.mp4
6. Univariate Analysis and EDD.vtt
6.1 03_04_PDE_Univariate_Analysis_Uni.pdf.pdf
7. EDD in R.mp4
7. EDD in R.vtt
8. Project Exercise 2.html
9. Outlier Treatment.mp4
9. Outlier Treatment.vtt
9.1 04_06_PDE_Outlier_Treatment.pdf.pdf
6. Linear Regression Model
1. The problem statement.mp4
1. The problem statement.vtt
1.1 05_01_Intro.pdf.pdf
10. Multiple Linear Regression in R.mp4
10. Multiple Linear Regression in R.vtt
11. Project Exercise 9.html
12. Test-Train split.mp4
12. Test-Train split.vtt
12.1 05_12_Test_Train.pdf.pdf
13. Bias Variance trade-off.mp4
13. Bias Variance trade-off.vtt
13.1 05_13_Bias_Var_tradeoff.pdf.pdf
14. Test-Train Split in R.mp4
14. Test-Train Split in R.vtt
15. Linear models other than OLS.mp4
15. Linear models other than OLS.vtt
15.1 05_09_Other_lin_model.pdf.pdf
16. Subset Selection techniques.mp4
16. Subset Selection techniques.vtt
16.1 05_10_Subset_Selection.pdf.pdf
17. Subset selection in R.mp4
17. Subset selection in R.vtt
18. Project Exercise 10.html
19. Shrinkage methods - Ridge Regression and The Lasso.mp4
19. Shrinkage methods - Ridge Regression and The Lasso.vtt
19.1 05_11_Shrinkage_methods.pdf.pdf
2. Basic equations and Ordinary Least Squared (OLS) method.mp4
2. Basic equations and Ordinary Least Squared (OLS) method.vtt
2.1 05_02_Simple_lin_reg.pdf.pdf
20. Ridge regression and Lasso in R.mp4
20. Ridge regression and Lasso in R.vtt
21. Project Exercise 11.html
22. Final Project Exercise.html
22.1 Movie_collection_test.csv.csv
23. Course Conclusion.html
3. Assessing Accuracy of predicted coefficients.mp4
3. Assessing Accuracy of predicted coefficients.vtt
3.1 05_03_Simple_lin_reg_Accuracy.pdf.pdf
4. Assessing Model Accuracy - RSE and R squared.mp4
4. Assessing Model Accuracy - RSE and R squared.vtt
4.1 05_03_Simple_lin_reg_Accuracy.pdf.pdf
5. Simple Linear Regression in R.mp4
5. Simple Linear Regression in R.vtt
6. Project Exercise 8.html
7. Multiple Linear Regression.mp4
7. Multiple Linear Regression.vtt
7.1 05_04_Multiple_lin_reg.pdf.pdf
8. The F - statistic.mp4
8. The F - statistic.vtt
8.1 05_05_F_stat.pdf.pdf
9. Interpreting result for categorical Variable.mp4
9. Interpreting result for categorical Variable.vtt
9.1 05_06_Cat_var.pdf.pdf
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