Algorithms for Dummies

Mueller, John Paul, Massaron, Luca



Algorithms For Dummies 2nd Edition will explain the basics of what algorithms are, how they work, where they are in our lives, and how to create them yourself. Whether you're an internet user who is curious about the way algorithms affect your online habits, or a computer science student who wants to build a foundation in understanding algorithms, this book can get you started in the right direction.


  • Use pure Python and avoid third party libraries.
  • Create a NumPy replacement in a separate chapter near the beginning that includes:
    • A matrix computation class for matrix operations
    • Special classes for certain operations, such stacking or queuing
  • Get rid of Anaconda and use Google Colab exclusively (this would get rid of the compatibility messages and significantly reduce the amount of introductory materials--we could possibly get rid of Chapter 3 or at least make it much smaller).
  • Modify the Downloading the Datasets and Example Code section of Chapter 3 specifically for Google Colab and place it at the end of Chapter 1 if we decide to get rid of Chapter 3.
  • Create an online repository for the datasets and source code, likely using GitHub. This would allow us to provide updates to the source code when readers find errors and ensure that the right versions of the datasets remain available.
  • Remove Chapter 4 entirely and point the reader to online tutorials instead (this was the most unpopular chapter in the book).
  • Use more step-by-step instructions when possible.
  • Add more graphics (I'm very good with mechanical type drawings and there is a lot to be said for graphs/charts).
  • Use more real world/historical examples if possible (they're extremely popular).
  • Add a chapter on logistic regression (quite a few of our readers have requested one since we already cover linear programming in Chapter 19).
  • Add other useful algorithms if space allows.


John Mueller has published more than 100 books on technology, data, and programming. John has a website and blog where he writes articles on technology and offers assistance alongside his published books.

Luca Massaron is a data scientist specializing in insurance and finance. A Google Developer Expert in machine learning, he has been involved in quantitative analysis and algorithms since 2000.