Genetic Algorithms and Machine Learning for Programmers
Create AI Models and Evolve Solutions
by Frances Buontempo
Self-driving cars, natural language recognition, and online
recommendation engines are all possible thanks to Machine Learning. Now
you can create your own genetic algorithms, nature-inspired swarms,
Monte Carlo simulations, cellular automata, and clusters. Learn how to
test your ML code and dive into even more advanced topics. If you are a
beginner-to-intermediate programmer keen to understand machine learning,
this book is for you.
Discover machine learning algorithms using a handful of self-contained
recipes. Build a repertoire of algorithms, discovering terms and
approaches that apply generally. Bake intelligence into your algorithms,
guiding them to discover good solutions to problems.
In this book, you will:
- Use heuristics and design fitness functions.
- Build genetic algorithms.
- Make nature-inspired swarms with ants, bees and particles.
- Create Monte Carlo simulations.
- Investigate cellular automata.
- Find minima and maxima, using hill climbing and simulated annealing.
- Try selection methods, including tournament and roulette wheels.
- Learn about heuristics, fitness functions, metrics, and clusters.
Test your code and get inspired to try new problems. Work through
scenarios to code your way out of a paper bag; an important skill for
any competent programmer. See how the algorithms explore and learn by
creating visualizations of each problem. Get inspired to design your own
machine learning projects and become familiar with the jargon.
What You Need
Code in C++ (>= C++11), Python (2.x or 3.x) and JavaScript (using
the HTML5 canvas). Also uses matplotlib and some open source libraries,
including SFML, Catch and Cosmic-Ray. These plotting and testing
libraries are not required but their use will give you a fuller
experience. Armed with just a text editor and compiler/interpreter for
your language of choice you can still code along from the general
algorithm descriptions.
Resources
Releases:
- P1.0 2019/01/17
- B4.0 2018/10/11
- B3.0 2018/10/03
- B2.0 2018/09/12
- Preface
- Who Is This Book For?
- What’s in This Book?
- Online Resources
- Acknowledgments
- Escape! Code Your Way Out of a Paper Bag
excerpt
- Let’s Begin
- Your Mission: Find a Way Out
- How to Help the Turtle Escape
- Let’s Save the Turtle
- Did It Work?
- Over to You
- Decide! Find the Paper Bag
- Your Mission: Learn from Data
- How to Grow a Decision Tree
- Let’s Find That Paper Bag
- Did It Work?
- Over to You
- Boom! Create a Genetic Algorithm
excerpt
- Your Mission: Fire Cannonballs
- How to Breed Solutions
- Let’s Fire Some Cannons
- Did It Work?
- Over to You
- Swarm! Build a Nature-Inspired Swarm
- Your Mission: Crowd Control
- How to Form a Swarm
- Let’s Make a Swarm
- Did It Work?
- Over to You
- Colonize! Discover Pathways
- Your Mission: Lay Pheromones
- How to Create Pathways
- Let’s March Some Ants
- Did It Work?
- Over to You
- Diffuse! Employ a Stochastic Model
- Your Mission: Make Small Random Steps
- How to Cause Diffusion
- Let’s Diffuse Some Particles
- Did It Work?
- Over to You
- Buzz! Converge on One Solution
- Your Mission: Beekeeping
- How to Feed the Bees
- Let’s Make Some Bees Swarm
- Did It Work?
- Over to You
- Alive! Create Artificial Life
- Your Mission: Make Cells Come Alive
- How to Create Artificial Life
- Let’s Make Cellular Automata
- Did It Work?
- Over to You
- Dream! Explore CA with GA
- Your Mission: Find the Best
- How to Explore a CA
- Let’s Find the Best Starting Row
- Did It Work?
- Over to You
- Optimize! Find the Best
- Your Mission: Move Turtles
- How to Get a Turtle into a Paper Bag
- Let’s Find the Bottom of the Bag
- Did It Work?
- Extension to More Dimensions
- Over to You
Author
Frances Buontempo is the editor of ACCU’s Overload magazine
(https://accu.org/index.php/journal/overload_by_cover). She has
published articles and given talks centered on technology and machine
learning. With a PhD in data mining, she has been programming
professionally since the 1990s. During her career as a programmer, she
has championed unit testing, mentored newer developers, deleted quite a
bit of code and fixed a variety of bugs.