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[FreeCourseSite.com] Udemy - ML for Business Managers Build Regression model in R Studio

文件类型 收录时间 最后活跃 资源热度 文件大小 文件数量
视频 2022-1-30 07:50 2024-11-19 20:14 344 2.77 GB 55
磁力链接
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迅雷链接
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FreeCourseSite com Udemy - ML for Business Managers Build Regression model in R Studio

文件列表
  1. 1. Introduction/1. Welcome to the course!.mp415.41MB
  2. 1. Introduction/3. Course contents.mp447.04MB
  3. 1. Introduction/4. This is a milestone!.mp420.68MB
  4. 2. Basics of Statistics/1. Types of Data.mp421.77MB
  5. 2. Basics of Statistics/2. Types of Statistics.mp410.93MB
  6. 2. Basics of Statistics/3. Describing the data graphically.mp465.37MB
  7. 2. Basics of Statistics/4. Measures of Centers.mp438.59MB
  8. 2. Basics of Statistics/6. Measures of Dispersion.mp422.87MB
  9. 3. Getting started with R and R studio/1. Installing R and R studio.mp440.84MB
  10. 3. Getting started with R and R studio/2. Basics of R and R studio.mp448.2MB
  11. 3. Getting started with R and R studio/3. Packages in R.mp498.68MB
  12. 3. Getting started with R and R studio/4. Inputting data part 1 Inbuilt datasets of R.mp446.15MB
  13. 3. Getting started with R and R studio/5. Inputting data part 2 Manual data entry.mp430.87MB
  14. 3. Getting started with R and R studio/6. Inputting data part 3 Importing from CSV or Text files.mp469.15MB
  15. 3. Getting started with R and R studio/7. Creating Barplots in R.mp4117.55MB
  16. 3. Getting started with R and R studio/8. Creating Histograms in R.mp451.51MB
  17. 4. Introduction to Machine Learning/1. Introduction to Machine Learning.mp4123.89MB
  18. 4. Introduction to Machine Learning/2. Building a Machine Learning model.mp445.28MB
  19. 5. Data Preprocessing/1. Gathering Business Knowledge.mp425.12MB
  20. 5. Data Preprocessing/10. Outlier Treatment in R.mp437.98MB
  21. 5. Data Preprocessing/12. Missing Value imputation.mp427.56MB
  22. 5. Data Preprocessing/13. Missing Value imputation in R.mp431.77MB
  23. 5. Data Preprocessing/15. Seasonality in Data.mp420.9MB
  24. 5. Data Preprocessing/16. Bi-variate Analysis and Variable Transformation.mp4113.76MB
  25. 5. Data Preprocessing/17. Variable transformation in R.mp467.86MB
  26. 5. Data Preprocessing/19. Non Usable Variables.mp423.95MB
  27. 5. Data Preprocessing/2. Data Exploration.mp423.41MB
  28. 5. Data Preprocessing/20. Dummy variable creation Handling qualitative data.mp440.61MB
  29. 5. Data Preprocessing/21. Dummy variable creation in R.mp452.26MB
  30. 5. Data Preprocessing/23. Correlation Matrix and cause-effect relationship.mp481.28MB
  31. 5. Data Preprocessing/24. Correlation Matrix in R.mp495.06MB
  32. 5. Data Preprocessing/3. The Data and the Data Dictionary.mp478.57MB
  33. 5. Data Preprocessing/4. Importing the dataset into R.mp415.99MB
  34. 5. Data Preprocessing/6. Univariate Analysis and EDD.mp427.3MB
  35. 5. Data Preprocessing/7. EDD in R.mp4112.27MB
  36. 5. Data Preprocessing/9. Outlier Treatment.mp427.76MB
  37. 6. Linear Regression Model/1. The problem statement.mp410.67MB
  38. 6. Linear Regression Model/10. Interpreting result for categorical Variable.mp427.16MB
  39. 6. Linear Regression Model/11. Multiple Linear Regression in R.mp473.1MB
  40. 6. Linear Regression Model/14. Test-Train split.mp449.16MB
  41. 6. Linear Regression Model/15. Bias Variance trade-off.mp429.59MB
  42. 6. Linear Regression Model/17. Test-Train Split in R.mp491.05MB
  43. 6. Linear Regression Model/2. Basic equations and Ordinary Least Squared (OLS) method.mp450.23MB
  44. 6. Linear Regression Model/3. Assessing Accuracy of predicted coefficients.mp4104.44MB
  45. 6. Linear Regression Model/4. Assessing Model Accuracy - RSE and R squared.mp449.74MB
  46. 6. Linear Regression Model/5. Simple Linear Regression in R.mp450.59MB
  47. 6. Linear Regression Model/7. Multiple Linear Regression.mp438.91MB
  48. 6. Linear Regression Model/8. The F - statistic.mp464.16MB
  49. 7. Regression models other than OLS/1. Linear models other than OLS.mp419.18MB
  50. 7. Regression models other than OLS/2. Subset Selection techniques.mp487.12MB
  51. 7. Regression models other than OLS/3. Subset selection in R.mp476.62MB
  52. 7. Regression models other than OLS/5. Shrinkage methods - Ridge Regression and The Lasso.mp438.68MB
  53. 7. Regression models other than OLS/6. Ridge regression and Lasso in R.mp4124.24MB
  54. 7. Regression models other than OLS/7. Heteroscedasticity.mp417.72MB
  55. 8. Conclusion/2. The final milestone!.mp411.86MB
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