This section comprises information regarding how to deal with imbalanced data and optimizing your algorithm for a practical bias/variance trade-off. It also goes deeper into more advanced algorithms, such as artificial neural networks and the ensemble methods.
This section comprises the following chapters:
- Chapter 7, Neural Networks – Here Comes Deep Learning
- Chapter 8 , Ensembles – When One Model Is Not Enough
- Chapter 9, The Y is as Important as the X
- Chapter 10, ...