In this chapter we will see the following recipes:
- Creating sample data for toy analysis
- Scaling data to the standard normal distribution
- Creating binary features through thresholding
- Working with categorical variables
- Imputing missing values through various strategies
- A linear model in the presence of outliers
- Putting it all together with pipelines
- Using Gaussian processes for regression
- Using SGD for regression
