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Python Data Structures and Algorithms

You're reading from  Python Data Structures and Algorithms

Product type Book
Published in May 2017
Publisher Packt
ISBN-13 9781786467355
Pages 310 pages
Edition 1st Edition
Languages
Author (1):
Benjamin Baka Benjamin Baka
Profile icon Benjamin Baka
Toc

Table of Contents (20) Chapters close

Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Python Objects, Types, and Expressions 2. Python Data Types and Structures 3. Principles of Algorithm Design 4. Lists and Pointer Structures 5. Stacks and Queues 6. Trees 7. Hashing and Symbol Tables 8. Graphs and Other Algorithms 9. Searching 10. Sorting 11. Selection Algorithms 12. Design Techniques and Strategies 13. Implementations, Applications, and Tools

Machine learning


Machine learning is a subfield of artificial intelligence. We know that we can never truly create machines that actually "think" but we can supply machines with enough data and models by which sound judgment can be reached. Machine learning focuses on creating autonomous systems that can continue the process of decision making, with little or no human intervention.

In order to teach the machine, we need data drawn from the real world. For instance, to shift through which e-mails constitute spam and which ones don't, we need to feed the machine with samples of each. After obtaining this data, we have to run the data through models (algorithms) that will use probability and statistics to unearth patterns and structure from the data. If this is properly done, the algorithm by itself will be able to analyze e-mails and properly categorize them. Sorting e-mails is just one example of what machines can do if they are "trained".

Types of machine learning

There are three broad categories...

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