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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

Appendix 1. Other Books You May Enjoy

If you enjoyed this book, you may be interested in these other books by Packt:

Applied Data Science with Python and JupyterAlex Galea

ISBN: 978-1-78995-817-1

  • Get up and running with the Jupyter ecosystem
  • Identify potential areas of investigation and perform exploratory data analysis
  • Plan a machine learning classification strategy and train classification models
  • Use validation curves and dimensionality reduction to tune and enhance your models
  • Scrape tabular data from web pages and transform it into Pandas DataFrames
  • Create interactive, web-friendly visualizations to clearly communicate your findings

Python Data Science Essentials - Third Edition Alberto Boschetti, Luca Massaron

ISBN: 978-1-78953-786-4

  • Set up your data science toolbox on Windows, Mac, and Linux
  • Use the core machine learning methods offered by the scikit-learn library
  • Manipulate, fix, and explore data to solve data science problems
  • Learn advanced explorative and manipulative techniques to solve data operations
  • Optimize your machine learning models for optimized performance
  • Explore and cluster graphs, taking advantage of interconnections and links in your data
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