This file summarized some important ML/DL algorithms, also data preprocessing is included And the corresponding program template is provided for each algorithm. Following the Udemy online course: Machine Learnign A-Z: hands on python & R in data science.
1.1 Import Data
1.2 Take Care of Missing Data(nan)
1.3 Encoding Categorical Data
1.4 Splitting the Data set to Training set and Test set
1.5 Feature Scaling
1.1 Linear Regression
1.2 Multivariable Linear Regression
1.3 Polynomial Regression
1.4 SVR(support vector regression)
1.5 Decision Tree Regression
1.6 Random Forest Regression