Free Books and Articles

For students interested in enhancing their Python skills, especially within the realm of data science, I recommend the following resources:

1. Think Python: How to Think Like a Computer Scientist by Allen B. Downey

• This book offers a comprehensive introduction to Python programming, tailored for newcomers to the language.

• Access the entire book for free: Think Python 2nd Edition.

• Main Topics Covered:

  • Variables, expressions and statements

  • Functions

  • Case study: interface design

  • Conditionals and recursion

  • Fruitful functions

  • Iteration

  • Strings

  • Case study: word play

  • Lists

  • Dictionaries

  • Tuples

  • Case study: data structure selection

  • Files

  • Classes and objects

  • Classes and functions

  • Classes and methods

  • Inheritance

  • The Goodies

  • Debugging

  • Analysis of Algorithms

2. Python Data Science Handbook by Jake VanderPlas

• An excellent online book covering essential tools for data science with Python, such as Jupyter, NumPy, Pandas, Matplotlib, and Scikit-Learn.

• Access the entire book for free: Python Data Science Handbook.

• Main Topics Covered:

  • Introduction to NumPy

  • Data Manipulation with Pandas

  • Visualization with Matplotlib

  • Machine Learning with Scikit-Learn

3. Applied Machine Learning in Python by Andreas C. Müller

• This book aims to provide an accessible introduction into applying machine learning with Python, in particular using the scikit-learn library.

• Access the entire book for free: Applied Machine Learning in Python

These resources are invaluable for our Knowledge Discovery and Data Mining class, ensuring you have a firm grasp on foundational Python concepts as well as advanced data science tools and techniques.