In this chapter, we learned about artificial neural networks. We discussed how to build and train neural networks. We talked about perceptrons and built a classifier based on that. We learned about single layer neural networks as well as multilayer neural networks. We discussed how neural networks could be used to build a vector quantizer. We analyzed sequential data using recurrent neural networks. We then built an optical character recognition engine using artificial neural networks. In the next chapter, we will learn about reinforcement learning and see how to build smart learning agents.
Artificial Intelligence with Python
Artificial Intelligence with Python
Overview of this book
Artificial Intelligence is becoming increasingly relevant in the modern world. By harnessing the power of algorithms, you can create apps which intelligently interact with the world around you, building intelligent recommender systems, automatic speech recognition systems and more.
Starting with AI basics you'll move on to learn how to develop building blocks using data mining techniques. Discover how to make informed decisions about which algorithms to use, and how to apply them to real-world scenarios. This practical book covers a range of topics including predictive analytics and deep learning.
Table of Contents (23 chapters)
Artificial Intelligence with Python
Credits
About the Author
About the Reviewer
www.PacktPub.com
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Preface
Free Chapter
Introduction to Artificial Intelligence
Classification and Regression Using Supervised Learning
Predictive Analytics with Ensemble Learning
Detecting Patterns with Unsupervised Learning
Building Recommender Systems
Logic Programming
Heuristic Search Techniques
Genetic Algorithms
Building Games With Artificial Intelligence
Natural Language Processing
Probabilistic Reasoning for Sequential Data
Building A Speech Recognizer
Object Detection and Tracking
Artificial Neural Networks
Reinforcement Learning
Deep Learning with Convolutional Neural Networks
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