4 Optimizing the training process: Underfitting, overfitting, testing, and regularization

In this chapter

  • what is underfitting and overfitting
  • some solutions for avoiding overfitting: testing, the model complexity graph, and regularization
  • calculating the complexity of the model using the L1 and L2 norms
  • picking the best model in terms of performance and complexity

This chapter is different from most of the chapters in this book, because it doesn’t contain a particular machine learning algorithm. Instead, it describes some potential problems that machine learning models may face and effective practical ways to solve them.

Imagine that you have ...

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