In this chapter, we will cover the following recipes:
- Building a linear classifier using support vector machines (SVMs)
- Building a nonlinear classifier using SVMs
- Tackling class imbalance
- Extracting confidence measurements
- Finding optimal hyperparameters
- Building an event predictor
- Estimating traffic
- Simplifying a machine learning workflow using TensorFlow
- Implementing the stacking method