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[DesireCourse.Com] Udemy - Machine Learning Basics Building a Regression model in R

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种子名称: [DesireCourse.Com] Udemy - Machine Learning Basics Building a Regression model in R
文件类型: 视频
文件数目: 52个文件
文件大小: 2.75 GB
收录时间: 2021-5-5 16:09
已经下载: 3
资源热度: 298
最近下载: 2024-12-23 08:32

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[DesireCourse.Com] Udemy - Machine Learning Basics Building a Regression model in R.torrent
  • 1. Introduction/1. Welcome to the course!.mp415.41MB
  • 1. Introduction/2. Course contents.mp447.04MB
  • 2. Basics of Statistics/1. Types of Data.mp425.86MB
  • 2. Basics of Statistics/2. Types of Statistics.mp413.24MB
  • 2. Basics of Statistics/3. Describing the data graphically.mp482.16MB
  • 2. Basics of Statistics/4. Measures of Centers.mp445.69MB
  • 2. Basics of Statistics/6. Measures of Dispersion.mp428.37MB
  • 3. Getting started with R and R studio/1. Installing R and R studio.mp440.83MB
  • 3. Getting started with R and R studio/2. Basics of R and R studio.mp448.2MB
  • 3. Getting started with R and R studio/3. Packages in R.mp498.67MB
  • 3. Getting started with R and R studio/4. Inputting data part 1 Inbuilt datasets of R.mp446.16MB
  • 3. Getting started with R and R studio/5. Inputting data part 2 Manual data entry.mp430.88MB
  • 3. Getting started with R and R studio/6. Inputting data part 3 Importing from CSV or Text files.mp469.14MB
  • 3. Getting started with R and R studio/7. Creating Barplots in R.mp4117.54MB
  • 3. Getting started with R and R studio/8. Creating Histograms in R.mp451.51MB
  • 4. Introduction to Machine Learning/1. Introduction to Machine Learning.mp4123.89MB
  • 4. Introduction to Machine Learning/2. Building a Machine Learning model.mp445.28MB
  • 5. Data Preprocessing/1. Gathering Business Knowledge.mp425.12MB
  • 5. Data Preprocessing/10. Outlier Treatment in R.mp437.98MB
  • 5. Data Preprocessing/12. Missing Value imputation.mp427.57MB
  • 5. Data Preprocessing/13. Missing Value imputation in R.mp431.76MB
  • 5. Data Preprocessing/15. Seasonality in Data.mp420.89MB
  • 5. Data Preprocessing/16. Bi-variate Analysis and Variable Transformation.mp4113.76MB
  • 5. Data Preprocessing/17. Variable transformation in R.mp467.86MB
  • 5. Data Preprocessing/19. Non Usable Variables.mp423.96MB
  • 5. Data Preprocessing/2. Data Exploration.mp423.42MB
  • 5. Data Preprocessing/20. Dummy variable creation Handling qualitative data.mp440.62MB
  • 5. Data Preprocessing/21. Dummy variable creation in R.mp452.27MB
  • 5. Data Preprocessing/23. Correlation Matrix and cause-effect relationship.mp481.29MB
  • 5. Data Preprocessing/24. Correlation Matrix in R.mp495.05MB
  • 5. Data Preprocessing/3. The Data and the Data Dictionary.mp478.58MB
  • 5. Data Preprocessing/4. Importing the dataset into R.mp415.99MB
  • 5. Data Preprocessing/6. Univariate Analysis and EDD.mp427.3MB
  • 5. Data Preprocessing/7. EDD in R.mp4112.26MB
  • 5. Data Preprocessing/9. Outlier Treatment.mp427.76MB
  • 6. Linear Regression Model/1. The problem statement.mp410.68MB
  • 6. Linear Regression Model/10. Multiple Linear Regression in R.mp473.1MB
  • 6. Linear Regression Model/12. Test-Train split.mp449.15MB
  • 6. Linear Regression Model/13. Bias Variance trade-off.mp429.59MB
  • 6. Linear Regression Model/14. Test-Train Split in R.mp491.05MB
  • 6. Linear Regression Model/15. Linear models other than OLS.mp419.18MB
  • 6. Linear Regression Model/16. Subset Selection techniques.mp487.11MB
  • 6. Linear Regression Model/17. Subset selection in R.mp476.61MB
  • 6. Linear Regression Model/19. Shrinkage methods - Ridge Regression and The Lasso.mp438.67MB
  • 6. Linear Regression Model/2. Basic equations and Ordinary Least Squared (OLS) method.mp450.23MB
  • 6. Linear Regression Model/20. Ridge regression and Lasso in R.mp4124.24MB
  • 6. Linear Regression Model/3. Assessing Accuracy of predicted coefficients.mp4104.43MB
  • 6. Linear Regression Model/4. Assessing Model Accuracy - RSE and R squared.mp449.74MB
  • 6. Linear Regression Model/5. Simple Linear Regression in R.mp450.6MB
  • 6. Linear Regression Model/7. Multiple Linear Regression.mp438.92MB
  • 6. Linear Regression Model/8. The F - statistic.mp464.16MB
  • 6. Linear Regression Model/9. Interpreting result for categorical Variable.mp427.16MB