Book Image

Getting Started with Python

By : Fabrizio Romano, Benjamin Baka, Dusty Phillips
Book Image

Getting Started with Python

By: Fabrizio Romano, Benjamin Baka, Dusty Phillips

Overview of this book

This Learning Path helps you get comfortable with the world of Python. It starts with a thorough and practical introduction to Python. You’ll quickly start writing programs, building websites, and working with data by harnessing Python's renowned data science libraries. With the power of linked lists, binary searches, and sorting algorithms, you'll easily create complex data structures, such as graphs, stacks, and queues. After understanding cooperative inheritance, you'll expertly raise, handle, and manipulate exceptions. You will effortlessly integrate the object-oriented and not-so-object-oriented aspects of Python, and create maintainable applications using higher level design patterns. Once you’ve covered core topics, you’ll understand the joy of unit testing and just how easy it is to create unit tests. By the end of this Learning Path, you will have built components that are easy to understand, debug, and can be used across different applications. This Learning Path includes content from the following Packt products: • Learn Python Programming - Second Edition by Fabrizio Romano • Python Data Structures and Algorithms by Benjamin Baka • Python 3 Object-Oriented Programming by Dusty Phillips
Table of Contents (31 chapters)
Title Page
Copyright and Credits
About Packt
Contributors
Preface
8
Stacks and Queues
10
Hashing and Symbol Tables
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