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Getting Started with Python

You're reading from   Getting Started with Python Understand key data structures and use Python in object-oriented programming

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Product type Course
Published in Feb 2019
Publisher Packt
ISBN-13 9781838551919
Length 722 pages
Edition 1st Edition
Languages
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Authors (3):
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Benjamin Baka Benjamin Baka
Author Profile Icon Benjamin Baka
Benjamin Baka
Fabrizio Romano Fabrizio Romano
Author Profile Icon Fabrizio Romano
Fabrizio Romano
Dusty Phillips Dusty Phillips
Author Profile Icon Dusty Phillips
Dusty Phillips
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Toc

Table of Contents (31) Chapters Close

Title Page
Copyright and Credits
About Packt
Contributors
Preface
1. A Gentle Introduction to Python FREE CHAPTER 2. Built-in Data Types 3. Iterating and Making Decisions 4. Functions, the Building Blocks of Code 5. Files and Data Persistence 6. Principles of Algorithm Design 7. Lists and Pointer Structures 8. Stacks and Queues 9. Trees 10. Hashing and Symbol Tables 11. Graphs and Other Algorithms 12. Searching 13. Sorting 14. Selection Algorithms 15. Object-Oriented Design 16. Objects in Python 17. When Objects Are Alike 18. Expecting the Unexpected 19. When to Use Object-Oriented Programming 20. Python Object-Oriented Shortcuts 21. The Iterator Pattern 22. Python Design Patterns I 23. Python Design Patterns II 24. Testing Object-Oriented Programs 1. Other Books You May Enjoy Index

Case study


One of the fields in which Python is the most popular these days is data science. In honor of that fact, let's implement a basic machine learning algorithm.

Machine learning is a huge topic, but the general idea is to make predictions or classifications about future data by using knowledge gained from past data. Uses of such algorithms abound, and data scientists are finding new ways to apply machine learning every day. Some important machine learning applications include computer vision (such as image classification or facial recognition), product recommendation, identifying spam, and self-driving cars.

So as not to digress into an entire book on machine learning, we'll look at a simpler problem: given an RGB color definition, what name would humans identify that color as?

There are more than 16 million colors in the standard RGB color space, and humans have come up with names for only a fraction of them. While there are thousands of names (some quite ridiculous; just go to any...

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