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Artificial Intelligence with Python

You're reading from   Artificial Intelligence with Python A Comprehensive Guide to Building Intelligent Apps for Python Beginners and Developers

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Product type Paperback
Published in Jan 2017
Publisher Packt
ISBN-13 9781786464392
Length 446 pages
Edition 1st Edition
Languages
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Author (1):
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Prateek Joshi Prateek Joshi
Author Profile Icon Prateek Joshi
Prateek Joshi
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Toc

Table of Contents (17) Chapters Close

Preface 1. Introduction to Artificial Intelligence FREE CHAPTER 2. Classification and Regression Using Supervised Learning 3. Predictive Analytics with Ensemble Learning 4. Detecting Patterns with Unsupervised Learning 5. Building Recommender Systems 6. Logic Programming 7. Heuristic Search Techniques 8. Genetic Algorithms 9. Building Games With Artificial Intelligence 10. Natural Language Processing 11. Probabilistic Reasoning for Sequential Data 12. Building A Speech Recognizer 13. Object Detection and Tracking 14. Artificial Neural Networks 15. Reinforcement Learning 16. Deep Learning with Convolutional Neural Networks

Summary


In this chapter, we learned how heuristic search techniques work. We discussed the difference between uninformed and informed search. We learned about constraint satisfaction problems and how we can solve problems using this paradigm. We discussed how local search techniques work and why simulated annealing is used in practice. We implemented greedy search for a string problem. We solved a problem using the CSP formulation.

We used this approach to solve the region-coloring problem. We then discussed the A* algorithm and how it can used to find the optimal paths to the solution. We used it to build an 8-puzzle solver as well as a maze solver. In the next chapter, we will discuss genetic algorithms and how they can used to solve real-world problems.

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