Genetic Algorithms and Machine Learning for Programmers
The Pragmatic Programmers (Verlag)
978-1-68050-620-4 (ISBN)
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.
Frances Buontempo is the editor of ACCU's Overload magazine. 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.
Preface
Who Is This Book For?
What’s in This Book?
Online Resources
Acknowledgments
Escape! Code Your Way Out of a Paper Bag
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
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
| Erscheinungsdatum | 06.02.2019 |
|---|---|
| Verlagsort | Raleigh |
| Sprache | englisch |
| Maße | 192 x 238 mm |
| Gewicht | 480 g |
| Einbandart | kartoniert |
| Themenwelt | Informatik ► Theorie / Studium ► Algorithmen |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Schlagworte | Algorithmen • Codebeispiele • Künstliche Intelligenz • Rezepte |
| ISBN-10 | 1-68050-620-X / 168050620X |
| ISBN-13 | 978-1-68050-620-4 / 9781680506204 |
| Zustand | Neuware |
| Haben Sie eine Frage zum Produkt? |
aus dem Bereich
