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种子名称： [FTUForum.com] [UDEMY] Machine Learning Basics Building a Regression model in R [FTU]
文件类型： 视频
文件数目： 52个文件
文件大小： 2.86 GB
收录时间： 2020-11-10 22:24
已经下载： 3次
资源热度： 143
最近下载： 2024-5-14 09:47

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[FTUForum.com] [UDEMY] Machine Learning Basics Building a Regression model in R [FTU].torrent

1. Introduction/1. Welcome to the course!.mp419.54MB

1. Introduction/2. Course contents.mp463.53MB

2. Basics of Statistics/1. Types of Data.mp441.25MB

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/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/1. Gathering Business Knowledge.mp425.12MB

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/2. Data Exploration.mp423.42MB

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/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.mp452.97MB

6. Linear Regression Model/1. The problem statement.mp410.68MB

6. Linear Regression Model/20. Ridge regression and Lasso in R.mp4181.06MB

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.mp449.74MB

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.mp464.17MB

6. Linear Regression Model/9. Interpreting result for categorical Variable.mp427.16MB