Book Image

Machine Learning Quick Reference

By : Rahul Kumar
Book Image

Machine Learning Quick Reference

By: Rahul Kumar

Overview of this book

Machine learning makes it possible to learn about the unknowns and gain hidden insights into your datasets by mastering many tools and techniques. This book guides you to do just that in a very compact manner. After giving a quick overview of what machine learning is all about, Machine Learning Quick Reference jumps right into its core algorithms and demonstrates how they can be applied to real-world scenarios. From model evaluation to optimizing their performance, this book will introduce you to the best practices in machine learning. Furthermore, you will also look at the more advanced aspects such as training neural networks and work with different kinds of data, such as text, time-series, and sequential data. Advanced methods and techniques such as causal inference, deep Gaussian processes, and more are also covered. By the end of this book, you will be able to train fast, accurate machine learning models at your fingertips, which you can easily use as a point of reference.
Table of Contents (18 chapters)
Title Page
Copyright and Credits
About Packt
Contributors
Preface
Index

Chapter 9. Selected Topics in Deep Learning

In Chapter 4Training Neural Networks, we looked at what an artificial neural network (ANN) is and how this kind of model is built. You can say that a deep neural network is an elongated version of an ANN; however, it has got its own set of challenges.

In this chapter, we will learn about the following topics:

  • What is a deep neural network?
  • How to initialize parameters
  • Adversarial networks—generative adversarial networks and Bayesian generative adversarial networks
  • Deep Gaussian processes
  • Hinton's Capsule network