To get the most out of this book

There are a couple of things you can do to get the most out of this book. Firstly, it is recommended to at least have some basic knowledge of Python programming and machine learning.

Secondly, before proceeding to Chapter 3, Getting Started with Neural Networks and others, be sure to follow the setup instructions in Chapter 2, Getting Yourself Ready for Deep Learning. You will also be able to set up your own environment as long as you can practice the given examples.

Thirdly, familiarized yourself with TensorFlow and read its documentation. The TensorFlow documentation (https://www.tensorflow.org/api_docs/) is a great source of information and also contains a lot of great examples and important examples. You can also look around online, as there are various open source examples and deep-learning-related resources.

Fourthly, make sure you explore on your own. Try different settings or configurations for simple problems that don't require much computational time; this can help you to quickly get some ideas of how the model works and how to tune parameters.

Lastly, dive deeper into each type of model. This book explains the gist of various deep learning models in plain words while avoiding too much math; the goal is to help you understand the mechanisms of neural networks under the hood. While there are currently many different tools publicly available that provide high-level APIs, a good understanding of deep leaning will greatly help you to debug and improve model performance.