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Python 3 Object-Oriented Programming

Python 3 Object-Oriented Programming

By : Dusty Phillips
4.3 (30)
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Python 3 Object-Oriented Programming

Python 3 Object-Oriented Programming

4.3 (30)
By: Dusty Phillips

Overview of this book

Object-oriented programming (OOP) is a popular design paradigm in which data and behaviors are encapsulated in such a way that they can be manipulated together. This third edition of Python 3 Object-Oriented Programming fully explains classes, data encapsulation, and exceptions with an emphasis on when you can use each principle to develop well-designed software. Starting with a detailed analysis of object-oriented programming, you will use the Python programming language to clearly grasp key concepts from the object-oriented paradigm. You will learn how to create maintainable applications by studying higher level design patterns. The book will show you the complexities of string and file manipulation, and how Python distinguishes between binary and textual data. Not one, but two very powerful automated testing systems, unittest and pytest, will be introduced in this book. You'll get a comprehensive introduction to Python's concurrent programming ecosystem. By the end of the book, you will have thoroughly learned object-oriented principles using Python syntax and be able to create robust and reliable programs confidently.
Table of Contents (15 chapters)
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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...

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