Who this book is for

This book is indented to provide the widest overview of deep learning, with Theano as support technology. The book is designed for the beginner in deep learning and artificial intelligence, as well as the computer programmer who wants to get a cross domain experience and become familiar with Theano and its supporting libraries. This book helps the reader to begin with deep learning, as well as getting the relevant and practical informations in deep learning.

Are required some basic skills in Python programming and computer science, as well as skills in elementary algebra and calculus. The underlying technology for all experiments is Theano, and the book provides first an in-depth presentation of the core technology first, then introduces later on some libraries to do some reuse of existing modules.

The approach of this book is to introduce the reader to deep learning, describing the different types of networks and their applications, and in the meantime, exploring the possibilities offered by Theano, a deep learning technology, that will be the support for all implementations. This book sums up some of the best performing nets and state of the art results and helps the reader get the global picture of deep learning, taking her from the simple to the complex nets gradually.

Since Python has become the main programming language in data science, this book tries to cover all that a Python programmer needs to know to do deep learning with Python and Theano.

The book will introduce two abstraction frameworks on top of Theano, Lasagne and Keras, which can simplify the development of more complex nets, but do not prevent you from understanding the underlying concepts.