Chapter 3. Getting started with neural networks


This chapter covers

  • Core components of neural networks
  • An introduction to Keras
  • Setting up a deep-learning workstation
  • Using neural networks to solve basic classification and regression problems

This chapter is designed to get you started with using neural networks to solve real problems. You’ll consolidate the knowledge you gained from our first practical example in chapter 2, and you’ll apply what you’ve learned to three new problems covering the three most common use cases of neural networks: binary classification, multiclass classification, and scalar regression.

In this chapter, we’ll take a closer look at the core components of neural networks that we introduced in chapter 2: layers, networks, objective functions, and optimizers. We’ll give you a quick introduction to Keras, the Python deep-learning library that we’ll use throughout the book. You’ll set up a deep-learning workstation, with TensorFlow, Keras, and GPU support. We’ll dive into three introductory examples of how to use neural networks to address real problems:

  • Classifying movie reviews as positive or negative (binary classification)
  • Classifying news wires by topic (multiclass classification)
  • Estimating the price of a house, given real-estate data (regression)

3.1. Anatomy of a neural network

3.2. Introduction to Keras

3.3. Setting up a deep-learning workstation

3.4. Classifying movie reviews: a binary classification example

3.5. Classifying newswires: a multiclass classification example

3.6. Predicting house prices: a regression example