In the first chapter, we talked about three different approaches to machine learning: supervised learning, unsupervised learning, and reinforcement learning. Classical neural networks are a type of supervised machine learning, though we will see later that deep learning popularity is instead due to the fact that modern deep neural networks can be used in unsupervised learning tasks as well. In the next chapter, we will highlight the main differences between classical shallow neural networks and deep neural nets. For now, however, we will mainly concentrate on classical feed-forward networks that work in a supervised way. Our first question is, what exactly is a neural network? Probably the best way to interpret a neural network is to describe it as a mathematical model for information processing. While this may seem rather vague, it will become much clearer in the next chapters. A neural net is not a fixed program, but rather a model, a system that processes information, or...
Python Deep Learning
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Python Deep Learning
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Overview of this book
With an increasing interest in AI around the world, deep learning has attracted a great deal of public attention. Every day, deep learning algorithms are used broadly across different industries.
The book will give you all the practical information available on the subject, including the best practices, using real-world use cases. You will learn to recognize and extract information to increase predictive accuracy and optimize results.
Starting with a quick recap of important machine learning concepts, the book will delve straight into deep learning principles using Sci-kit learn. Moving ahead, you will learn to use the latest open source libraries such as Theano, Keras, Google's TensorFlow, and H20. Use this guide to uncover the difficulties of pattern recognition, scaling data with greater accuracy and discussing deep learning algorithms and techniques.
Whether you want to dive deeper into Deep Learning, or want to investigate how to get more out of this powerful technology, you’ll find everything inside.
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Table of Contents (18 chapters)
Python Deep Learning
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
Free Chapter
Machine Learning – An Introduction
Neural Networks
Deep Learning Fundamentals
Unsupervised Feature Learning
Image Recognition
Recurrent Neural Networks and Language Models
Deep Learning for Board Games
Deep Learning for Computer Games
Anomaly Detection
Building a Production-Ready Intrusion Detection System
Index
Customer Reviews