Section 2: Advanced Supervised Learning – Hands-On Machine Learning with scikit-learn and Scientific Python Toolkits

Section 2: Advanced Supervised Learning

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, Imbalanced Learning – Not Even 1% Win the Lottery