Book Image

Deep Learning Essentials

By : Wei Di, Jianing Wei, Anurag Bhardwaj
3 (1)
Book Image

Deep Learning Essentials

3 (1)
By: Wei Di, Jianing Wei, Anurag Bhardwaj

Overview of this book

Deep Learning a trending topic in the field of Artificial Intelligence today and can be considered to be an advanced form of machine learning. This book will help you take your first steps in training efficient deep learning models and applying them in various practical scenarios. You will model, train, and deploy different kinds of neural networks such as CNN, RNN, and will see some of their applications in real-world domains including computer vision, natural language processing, speech recognition, and so on. You will build practical projects such as chatbots, implement reinforcement learning to build smart games, and develop expert systems for image captioning and processing using Python library such as TensorFlow. This book also covers solutions for different problems you might come across while training models, such as noisy datasets, and small datasets. By the end of this book, you will have a firm understanding of the basics of deep learning and neural network modeling, along with their practical applications.
Table of Contents (12 chapters)

Implementing reinforcement learning

In this section, we will look at how to implement a simple reinforcement learning method. We will use OpenAI's open source toolkits, gym and universe, for this purpose. gym is a software framework for developing and comparing different reinforcement learning algorithms. It supports environments for different games by Atari, board games, as well as classic control tasks. universe on the other hand provides a wrapper on top of gym with modules for client and server, where you can visualize the progress of a reinforcement learning system. To install these toolkits on a macbook, we do the following:

pip install gym
brew install golang libjpeg-turbo
pip install universe

Simple reinforcement learning example

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