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Genetic Algorithms and Machine Learning; also August PragPub

August 01, 2018

Welcome to August! On this day in 1981, MTV launched with their inaugural music video, "Video Killed the Radio Star" by The Buggles. Radio? Video? What, no mp3? Curious how systems evolve, isn't it? Speaking of evolution…

This week we are proud to release the beta of Genetic Algorithms and Machine Learning for Programmers: Create AI Models and Evolve Solutions, now available from

Are you up to speed on the basics of machine learning? Now's your chance. Come and evolve your skills today, or else you might end up as outdated as an '80s music video.

Strange Loop!

The Pragmatic Bookshelf will be at Strange Loop in St. Louis, September 26—28. Meet with one of our editors and find out more about our books. If you're interested in becoming an author, discuss your ideas with us and find out what it's like to write with Pragmatic. Tickets are still available. See the schedule here:

Genetic Algorithms and Machine Learning for Programmers: Create AI Models and Evolve Solutions

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.

Now in beta from

August PragPub Magazine

Giving back. Or paying it forward. However you describe it, sharing what you know is a natural thing to do. When you learn something hard, it’s inevitable that you will want to share what you learned. Explain a process to a colleague. Write an article or a book. Record a video. Build a tool and share it on Github. Conduct a class. Tutor a child. One-on-one or broadcast, you’re driven, somehow, to share what you know. It’s like your brain is a tool that knowledge uses to replicate itself.

Two articles this month deal with sharing knowledge. Andy Lester built a command-line tool that he found useful. He shared it as an open-source project and a lot of other people found it useful. Years later, he’s still maintaining it and people are still finding it useful. And yet he sometimes recommends what might be considered “competing” projects. Because gifts are most appreciated when you consider the recipient.

Then there’s Chris Strom. He’s sharing, too. He teaches kids game programming—in part, through his book 3D Game Programming for Kids. Chris has thought a lot about how to teach programming through games and how to teach JavaScript to beginning programmers. He, too, has learned that you need to consider carefully the recipient of your gift, and he comes to some counterintuitive conclusions about the virtue of new language features when it comes to teaching.

Russ Olsen is very much in sharing mode this month with a helpful and entertaining tutorial on floating-point math. It touches on infinities and infinities of infinities and the fact that numbers inside computers are models of real-world entities every bit as much as an Employee object is merely a model of a real-world person, and does it all without making your eyes glaze over.

Mike continues his computer history series with a look at how the investment in this radical new idea began to pay off. Herman Hollerith saves the U.S. Census from imminent disaster, Univac predicts the winner of the 1952 presidential election live on national television, John Mauchly invents a programming language, Grace Hopper invents a programming language you don’t have to be an engineer to use, and two Thomas Watsons, father and son, invest massively in R&D to stay ahead of the competition.

Also in this August issue: Marcus Blankenship deals with dealing with unreasonable feature requests, John Shade casts shade on the Citizen Developer, Mike interviews Andy Hunt about his science fiction books, and more.

We hope you enjoy it!

Now available from

Upcoming Author Appearances

  • 2018-08-06 Diana Larsen,
    Agile 2018, San Diego, CA
  • 2018-08-08 Diana Larsen,
    Agile 2018, San Diego, CA
  • 2018-08-09 Randall Koutnik,
  • 2018-08-16 VM Brasseur,
    REdeploy, San Francisco, CA
  • 2018-08-29 VM Brasseur,
    Open Source Summit North America, Vancouver, BC
  • 2018-09-03 Christina Moulton, Teak Mobile Inc.,
    try! Swift NYC
  • 2018-09-14 VM Brasseur,
    Cascadia PHP
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    Coming Soon:

    • Property-Based Testing with PropEr, Erlang, and Elixir: Find Bugs Before Your Users Do, in beta
    • Swift Style, Second Edition, in beta
    • Practical Chatbots, in beta
    • Modern Systems Programming with Scala Native: Write Lean, High-Performance Code without the JVM, in beta

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