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[ FreeCourseWeb ] Udemy - Machine Learning Basics- Building a Regression model in R
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52个文件
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2.75 GB
收录时间:
2019-3-31 13:18
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最近下载:
2024-8-16 03:01
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[ FreeCourseWeb ] Udemy - Machine Learning Basics- Building a Regression model in R.torrent
6. Linear Regression Model/20. Ridge regression and Lasso in R.mp4124.24MB
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.mp445.68MB
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.mp448.19MB
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.mp446.15MB
3. Getting started with R and R studio/5. Inputting data part 2 Manual data entry.mp430.87MB
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.mp451.5MB
4. Introduction to Machine Learning/1. Introduction to Machine Learning.mp4123.88MB
4. Introduction to Machine Learning/2. Building a Machine Learning model.mp445.27MB
5. Data Preprocessing/1. Gathering Business Knowledge.mp425.11MB
5. Data Preprocessing/2. Data Exploration.mp423.41MB
5. Data Preprocessing/3. The Data and the Data Dictionary.mp478.57MB
5. Data Preprocessing/4. Importing the dataset into R.mp415.98MB
5. Data Preprocessing/6. Univariate Analysis and EDD.mp427.29MB
5. Data Preprocessing/7. EDD in R.mp4112.26MB
5. Data Preprocessing/9. Outlier Treatment.mp427.76MB
5. Data Preprocessing/10. Outlier Treatment in R.mp437.97MB
5. Data Preprocessing/12. Missing Value imputation.mp427.56MB
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.mp467.85MB
5. Data Preprocessing/19. Non Usable Variables.mp423.95MB
5. Data Preprocessing/20. Dummy variable creation Handling qualitative data.mp440.61MB
5. Data Preprocessing/21. Dummy variable creation in R.mp452.26MB
5. Data Preprocessing/23. Correlation Matrix and cause-effect relationship.mp481.28MB
5. Data Preprocessing/24. Correlation Matrix in R.mp495.05MB
6. Linear Regression Model/1. The problem statement.mp410.67MB
6. Linear Regression Model/2. Basic equations and Ordinary Least Squared (OLS) method.mp450.23MB
6. Linear Regression Model/3. Assessing Accuracy of predicted coefficients.mp4104.43MB
6. Linear Regression Model/4. Assessing Model Accuracy - RSE and R squared.mp449.73MB
6. Linear Regression Model/5. Simple Linear Regression in R.mp450.59MB
6. Linear Regression Model/7. Multiple Linear Regression.mp438.91MB
6. Linear Regression Model/8. The F - statistic.mp464.16MB
6. Linear Regression Model/9. Interpreting result for categorical Variable.mp427.15MB
6. Linear Regression Model/10. Multiple Linear Regression in R.mp473.09MB
6. Linear Regression Model/12. Test-Train split.mp449.15MB
6. Linear Regression Model/13. Bias Variance trade-off.mp429.58MB
6. Linear Regression Model/14. Test-Train Split in R.mp491.04MB
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