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The Python Workshop Second Edition - Second Edition

You're reading from  The Python Workshop Second Edition - Second Edition

Product type Book
Published in Nov 2022
Publisher Packt
ISBN-13 9781804610619
Pages 600 pages
Edition 2nd Edition
Languages
Authors (5):
Corey Wade Corey Wade
Profile icon Corey Wade
Mario Corchero Jiménez Mario Corchero Jiménez
Profile icon Mario Corchero Jiménez
Andrew Bird Andrew Bird
Profile icon Andrew Bird
Dr. Lau Cher Han Dr. Lau Cher Han
Profile icon Dr. Lau Cher Han
Graham Lee Graham Lee
Profile icon Graham Lee
View More author details

Table of Contents (16) Chapters

Preface 1. Chapter 1: Python Fundamentals – Math, Strings, Conditionals, and Loops 2. Chapter 2: Python Data Structures 3. Chapter 3: Executing Python – Programs, Algorithms, and Functions 4. Chapter 4: Extending Python, Files, Errors, and Graphs 5. Chapter 5: Constructing Python – Classes and Methods 6. Chapter 6: The Standard Library 7. Chapter 7: Becoming Pythonic 8. Chapter 8: Software Development 9. Chapter 9: Practical Python – Advanced Topics 10. Chapter 10: Data Analytics with pandas and NumPy 11. Chapter 11: Machine Learning 12. Chapter 12: Deep Learning with Python 13. Chapter 13: The Evolution of Python – Discovering New Python Features 14. Index 15. Other Books You May Enjoy

Introduction

Computer algorithms enable machines to learn from data. The more data an algorithm receives, the more capable the algorithm is of detecting underlying patterns within the data. In Chapter 10, Data Analytics with pandas and NumPy, you learned how to view and analyze big data with pandas and NumPy. In this chapter, we will now extend these concepts to algorithms that learn from data.

Consider how a child learns to identify a cat. Generally speaking, a child learns by having someone point out “That’s a cat”, “No, that’s a dog”, and so on. After enough cats and non-cats have been pointed out, the child knows how to identify a cat.

ML implements the same general approach. A convolutional neural network (CNN) is an ML algorithm that distinguishes between images. Upon receiving images labeled cats and non-cats, the algorithm looks for underlying patterns within the pixels by adjusting the parameters of an equation until it finds...

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