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文档列表

7. Regression models other than OLS/6. Ridge regression and Lasso in R.mp4 130.3 MB
4. Introduction to Machine Learning/1. Introduction to Machine Learning.mp4 129.9 MB
3. Getting started with R and R studio/7. Creating Barplots in R.mp4 123.3 MB
5. Data Preprocessing/16. Bi-variate Analysis and Variable Transformation.mp4 119.3 MB
5. Data Preprocessing/7. EDD in R.mp4 117.7 MB
6. Linear Regression Model/3. Assessing Accuracy of predicted coefficients.mp4 109.5 MB
3. Getting started with R and R studio/3. Packages in R.mp4 103.5 MB
5. Data Preprocessing/24. Correlation Matrix in R.mp4 99.7 MB
6. Linear Regression Model/16. Test-Train Split in R.mp4 95.5 MB
7. Regression models other than OLS/2. Subset Selection techniques.mp4 91.3 MB
2. Basics of Statistics/3. Describing the data graphically.mp4 86.2 MB
5. Data Preprocessing/23. Correlation Matrix and cause-effect relationship.mp4 85.2 MB
5. Data Preprocessing/3. The Data and the Data Dictionary.mp4 82.4 MB
7. Regression models other than OLS/3. Subset selection in R.mp4 80.3 MB
6. Linear Regression Model/11. Multiple Linear Regression in R.mp4 76.7 MB
3. Getting started with R and R studio/6. Inputting data part 3 Importing from CSV or Text files.mp4 72.5 MB
5. Data Preprocessing/17. Variable transformation in R.mp4 71.1 MB
6. Linear Regression Model/8. The F - statistic.mp4 67.3 MB
5. Data Preprocessing/21. Dummy variable creation in R.mp4 54.8 MB
3. Getting started with R and R studio/8. Creating Histograms in R.mp4 54.0 MB
6. Linear Regression Model/5. Simple Linear Regression in R.mp4 53.1 MB
6. Linear Regression Model/2. Basic equations and Ordinary Least Squared (OLS) method.mp4 52.7 MB
6. Linear Regression Model/4. Assessing Model Accuracy - RSE and R squared.mp4 52.1 MB
6. Linear Regression Model/14. Test-Train split.mp4 51.5 MB
3. Getting started with R and R studio/2. Basics of R and R studio.mp4 50.5 MB
1. Introduction/3. Course contents.mp4 49.3 MB
3. Getting started with R and R studio/4. Inputting data part 1 Inbuilt datasets of R.mp4 48.4 MB
2. Basics of Statistics/4. Measures of Centers.mp4 47.9 MB
4. Introduction to Machine Learning/2. Building a Machine Learning model.mp4 47.5 MB
3. Getting started with R and R studio/1. Installing R and R studio.mp4 42.8 MB
5. Data Preprocessing/20. Dummy variable creation Handling qualitative data.mp4 42.6 MB
6. Linear Regression Model/7. Multiple Linear Regression.mp4 40.8 MB
7. Regression models other than OLS/5. Shrinkage methods - Ridge Regression and The Lasso.mp4 40.5 MB
5. Data Preprocessing/10. Outlier Treatment in R.mp4 39.8 MB
5. Data Preprocessing/13. Missing Value imputation in R.mp4 33.3 MB
3. Getting started with R and R studio/5. Inputting data part 2 Manual data entry.mp4 32.4 MB
6. Linear Regression Model/15. Bias Variance trade-off.mp4 31.0 MB
2. Basics of Statistics/6. Measures of Dispersion.mp4 29.8 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 Model/9. Interpreting result for categorical Variable.mp4 28.5 MB
2. Basics of Statistics/1. Types of Data.mp4 27.1 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
5. Data Preprocessing/15. Seasonality in Data.mp4 21.9 MB
7. Regression models other than OLS/1. Linear models other than OLS.mp4 20.1 MB
7. Regression models other than OLS/7. Heteroscedasticity.mp4 18.6 MB
5. Data Preprocessing/4. Importing the dataset into R.mp4 16.8 MB
1. Introduction/1. Welcome to the course!.mp4 16.2 MB
2. Basics of Statistics/2. Types of Statistics.mp4 13.9 MB
6. Linear Regression Model/1. The problem statement.mp4 11.2 MB
1. Introduction/2.1 Files_linear_r.zip 9.0 MB
4. Introduction to Machine Learning/1.1 Lecture_machineLearning.pdf 1.0 MB
4. Introduction to Machine Learning/2.1 Lecture_machineLearning.pdf 1.0 MB
1. Introduction/3.1 00_Introduction_01.pdf 810.5 kB
2. Basics of Statistics/5.1 Exercise 1.pdf 567.1 kB
2. 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 Model/3.1 05_03_Simple_lin_reg_Accuracy.pdf 340.7 kB
6. Linear Regression Model/4.1 05_03_Simple_lin_reg_Accuracy.pdf 340.7 kB
5. Data Preprocessing/3.2 03_03_PDE_Raw_Data_Analysis_Uni.pdf 339.9 kB
6. Linear Regression Model/8.1 05_05_F_stat.pdf 336.4 kB
5. Data Preprocessing/12.1 04_05_PDE_Missing_value.pdf 333.5 kB
5. Data Preprocessing/2.1 03_02_PDE_Data_exploration.pdf 330.7 kB
2. Basics of Statistics/3.1 01_03_Lecture_DataSummaryandGraph.pdf 325.5 kB
2. Basics of Statistics/4.1 01_04_Lecture_Centers.pdf 320.5 kB
6. Linear Regression Model/2.1 05_02_Simple_lin_reg.pdf 291.6 kB
5. Data Preprocessing/23.1 04_10_Correlation.pdf 263.1 kB
6. Linear Regression Model/1.1 05_01_Intro.pdf 245.1 kB
6. Linear Regression Model/14.1 05_12_Test_Train.pdf 244.5 kB
6. Linear Regression Model/7.1 05_04_Multiple_lin_reg.pdf 225.1 kB
2. Basics of Statistics/6.1 01_05_Lecture_Dispersion.pdf 215.6 kB
6. Linear Regression Model/15.1 05_13_Bias_Var_tradeoff.pdf 207.2 kB
7. Regression models other than OLS/2.1 05_10_Subset_Selection.pdf 203.3 kB
7. Regression models other than OLS/5.1 05_11_Shrinkage_methods.pdf 192.6 kB
2. Basics of Statistics/1.1 01_01_Lecture_TypesOfData.pdf 182.0 kB
2. 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
7. Regression models other than OLS/1.1 05_09_Other_lin_model.pdf 160.3 kB
6. Linear Regression Model/9.1 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
3. Getting started with R and R studio/6.1 Customer.csv 65.6 kB
5. Data Preprocessing/3.1 House_Price.csv 54.8 kB
5. Data Preprocessing/4.2 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 23.8 kB
5. Data Preprocessing/16. Bi-variate Analysis and Variable Transformation.srt 18.7 kB
3. Getting started with R and R studio/7. Creating Barplots in R.srt 18.6 kB
6. Linear Regression Model/3. Assessing Accuracy of predicted coefficients.srt 16.2 kB
3. Getting started with R and R studio/3. Packages in R.srt 14.7 kB
3. Getting started with R and R studio/2. Basics of R and R studio.srt 14.6 kB
2. Basics of Statistics/3. Describing the data graphically.srt 13.2 kB
7. Regression models other than OLS/2. Subset Selection techniques.srt 13.1 kB
4. Introduction to Machine Learning/2. Building a Machine Learning model.srt 13.1 kB
8. Conclusion/1.1 Movie_collection_test.csv 12.0 kB
5. Data Preprocessing/7. EDD in R.srt 11.8 kB
7. Regression models other than OLS/6. Ridge regression and Lasso in R.srt 11.7 kB
5. Data Preprocessing/23. Correlation Matrix and cause-effect relationship.srt 11.3 kB
1. Introduction/3. Course contents.srt 10.4 kB
6. Linear Regression Model/14. Test-Train split.srt 10.3 kB
6. Linear Regression Model/2. Basic equations and Ordinary Least Squared (OLS) method.srt 10.1 kB
5. Data Preprocessing/24. Correlation Matrix in R.srt 9.3 kB
5. Data Preprocessing/17. Variable transformation in R.srt 9.3 kB
6. Linear Regression Model/8. The F - statistic.srt 9.2 kB
6. Linear Regression Model/16. Test-Train Split in R.srt 8.6 kB
3. Getting started with R and R studio/6. Inputting data part 3 Importing from CSV or Text files.srt 8.5 kB
6. Linear Regression Model/11. Multiple Linear Regression in R.srt 8.3 kB
7. Regression models other than OLS/5. Shrinkage methods - Ridge Regression and The Lasso.srt 8.2 kB
6. Linear Regression Model/4. Assessing Model Accuracy - RSE and R squared.srt 8.2 kB
6. Linear Regression Model/5. Simple Linear Regression in R.srt 8.2 kB
5. Data Preprocessing/3. The Data and the Data Dictionary.srt 8.0 kB
7. Regression models other than OLS/3. Subset selection in R.srt 7.8 kB
3. Getting started with R and R studio/8. Creating Histograms in R.srt 7.7 kB
3. Getting started with R and R studio/1. Installing R and R studio.srt 7.5 kB
2. Basics of Statistics/4. Measures of Centers.srt 7.4 kB
6. Linear Regression Model/15. Bias Variance trade-off.srt 6.6 kB
6. Linear Regression Model/7. Multiple Linear Regression.srt 5.9 kB
3. Getting started with R and R studio/4. Inputting data part 1 Inbuilt datasets of R.srt 5.6 kB
5. Data Preprocessing/19. Non Usable Variables.srt 5.5 kB
2. Basics of Statistics/6. Measures of Dispersion.srt 5.5 kB
6. Linear Regression Model/9. Interpreting result for categorical Variable.srt 5.4 kB
5. Data Preprocessing/21. Dummy variable creation in R.srt 5.3 kB
2. Basics of Statistics/1. Types of Data.srt 5.0 kB
5. Data Preprocessing/20. Dummy variable creation Handling qualitative data.srt 5.0 kB
5. Data Preprocessing/9. Outlier Treatment.srt 4.6 kB
7. Regression models other than OLS/1. Linear models other than OLS.srt 4.5 kB
5. Data Preprocessing/10. Outlier Treatment in R.srt 4.4 kB
5. Data Preprocessing/12. Missing Value imputation.srt 4.2 kB
5. Data Preprocessing/1. Gathering Business Knowledge.srt 4.0 kB
5. Data Preprocessing/15. Seasonality in Data.srt 3.9 kB
3. Getting started with R and R studio/5. Inputting data part 2 Manual data entry.srt 3.7 kB
5. Data Preprocessing/2. Data Exploration.srt 3.7 kB
5. Data Preprocessing/13. Missing Value imputation in R.srt 3.5 kB
5. Data Preprocessing/6. Univariate Analysis and EDD.srt 3.5 kB
1. Introduction/1. Welcome to the course!.srt 3.5 kB
2. Basics of Statistics/2. Types of Statistics.srt 3.1 kB
7. Regression models other than OLS/7. Heteroscedasticity.srt 2.7 kB
5. Data Preprocessing/4. Importing the dataset into R.srt 2.7 kB
8. Conclusion/3. Bonus Lecture.html 1.7 kB
6. Linear Regression Model/1. The problem statement.srt 1.7 kB
5. Data Preprocessing/4.1 R_Linear.zip 1.2 kB
8. Conclusion/2. Course Conclusion.html 946 Bytes
5. Data Preprocessing/5. Project Exercise 1.html 447 Bytes
7. Regression models other than OLS/8. Project Exercise 11.html 398 Bytes
2. Basics of Statistics/5. Practice Exercise 1.html 354 Bytes
8. Conclusion/1. Final Project Exercise.html 329 Bytes
6. Linear Regression Model/13. Project Exercise 9.html 328 Bytes
6. Linear Regression Model/6. Project Exercise 8.html 322 Bytes
2. Basics of Statistics/7. Practice Exercise 2.html 295 Bytes
5. Data Preprocessing/25. Project Exercise 7.html 288 Bytes
5. Data Preprocessing/18. Project Exercise 5.html 286 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
7. Regression models other than OLS/4. Project Exercise 10.html 199 Bytes
5. Data Preprocessing/8. Project Exercise 2.html 177 Bytes
4. Introduction to Machine Learning/3. Introduction to Machine learning quiz.html 167 Bytes
6. Linear Regression Model/10. Quiz.html 167 Bytes
6. Linear Regression Model/12. Quiz.html 167 Bytes
6. Linear Regression Model/17. Quiz.html 167 Bytes
1. Introduction/2. Course Resources.html 117 Bytes
0. Websites you may like/[FreeCourseWorld.Com].url 54 Bytes
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0. Websites you may like/[DesireCourse.Net].url 51 Bytes
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0. Websites you may like/[CourseClub.Me].url 48 Bytes
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