In this chapter, we have learned the concepts behind reinforcement learning, and how it can be used to build deep learning networks with Keras that learn how to play arcade games based on reward feedback. From there, we moved on to briefly discuss advances in this field, such as networks that have been taught to play harder games such as Go and Poker at a superhuman level. While game playing might seem like a frivolous application, these ideas are the first step towards general artificial intelligence, where a network learns from experience rather than large amounts of training data.
Deep Learning with Keras
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Deep Learning with Keras
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Overview of this book
This book starts by introducing you to supervised learning algorithms such as simple linear regression, the classical multilayer perceptron and more sophisticated deep convolutional networks. You will also explore image processing with recognition of handwritten digit images, classification of images into different categories, and advanced objects recognition with related image annotations. An example of identification of salient points for face detection is also provided.
Next you will be introduced to Recurrent Networks, which are optimized for processing sequence data such as text, audio or time series. Following that, you will learn about unsupervised learning algorithms such as Autoencoders and the very popular Generative Adversarial Networks (GANs). You will also explore non-traditional uses of neural networks as Style Transfer.
Finally, you will look at reinforcement learning and its application to AI game playing, another popular direction of research and application of neural networks.
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Current Title:
Deep Learning with Keras
Table of Contents (16 chapters)
Title Page
Credits
About the Authors
About the Reviewer
www.PacktPub.com
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Preface
Free Chapter
Neural Networks Foundations
Keras Installation and API
Deep Learning with ConvNets
Generative Adversarial Networks and WaveNet
Word Embeddings
Recurrent Neural Network — RNN
Additional Deep Learning Models
AI Game Playing
Conclusion
Customer Reviews