Algorithms for the Adventurous

Creative Solutions to Computational (and Human) Problems
by Bradford Tuckfield
November 2020, 248 pp.
ISBN-13: 
9781718500686
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Download Chapter 2: ALGORITHMS IN HISTORY

TAKE LIFE BY THE ALGORITHMS

What do catching a fly ball, filing your taxes, and baking a cake have in common? They’re all algorithms – sets of instructions – in action. Algorithms are everywhere; master them, and you’ll not only be better at using computers, you’ll be better at life.

Algorithms for the Adventurous unravels the complexities that belie the algorithmic approach to solving problems. It’s a fun, lively introduction to the subject that will take you around the globe and back through time. Along the way, you’ll become familiar with algorithmic procedures like searching, sorting, and optimization, and develop your ability to implement popular methods used in machine learning and artificial intelligence (AI). You’ll also learn:

  • Algorithms for debugging code, maximizing revenue, scheduling tasks, and decision trees
  • How to measure the efficiency and speed of algorithms
  • The subconscious algorithms governing human behavior, and what they teach us about designing computer algorithms
  • How to generate Voronoi diagrams, useful in a variety of geometric applications
  • How to use algorithms to create a simple chatbot or play a game

The book is packed with illustrative examples of functioning code written in the latest version of Python, with each snippet thoroughly explained and easily adaptable to a variety of uses. More importantly, you’ll discover that algorithms help us organize the world around us. Just as they’re instructive to computers, they’re instructive in optimizing our daily lives – but only if you’re adventurous enough to use them.

Author Bio 

Bradford Tuckfield, PhD, is the founder of Kmbara, which solves problems using machine learning, AI, chatbots, and other data-based innovations. The author of Applied Unsupervised Learning with R, his work has also been featured in top scholarly journals, and his essays on culture and public policy can be seen in Quillette, National Affairs, and other prestigious outlets.

Table of contents 

Acknowledgments
Introduction
Chapter 1: Problem-Solving With Algorithms
Chapter 2: Algorithms in History
Chapter 3: Maximizing and Minimizing
Chapter 4: Sorting and Searching
Chapter 5: Pure Math
Chapter 6: Advanced Optimization
Chapter 7: Geometry
Chapter 8: Language
Chapter 9: Machine Learning
Chapter 10: Artificial Intelligence
Chapter 11: Forging Ahead
Index

View the detailed Table of Contents