- Computers / Programming / Algorithms
- Computers / Intelligence (AI) & Semantics
- Computers / Neural Networks
Grokking Artificial Intelligence Algorithms
| Author(s) | Rishal Hurbans |
| Publisher | Simon and Schuster |
| Published | 2020-09-01 |
| ISBN | 9781617296185 |
| Page Count | 392 |
| Language | en |
| Add Book | |
Grokking Artificial Intelligence Algorithms is a fully-illustrated and interactive tutorial guide to the different approaches and algorithms that underpin AI. Written in simple language and with lots of visual references and hands-on examples, you’ll learn the concepts, terminology, and theory you need to effectively incorporate AI algorithms into your applications.
Summary
Grokking Artificial Intelligence Algorithms is a fully-illustrated and interactive tutorial guide to the different approaches and algorithms that underpin AI. Written in simple language and with lots of visual references and hands-on examples, you’ll learn the concepts, terminology, and theory you need to effectively incorporate AI algorithms into your applications. And to make sure you truly grok as you go, you’ll use each algorithm in practice with creative coding exercises—including building a maze puzzle game, performing diamond data analysis, and even exploring drone material optimization.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
About the technology
Artificial intelligence touches every part of our lives. It powers our shopping and TV recommendations; it informs our medical diagnoses. Embracing this new world means mastering the core algorithms at the heart of AI.
About the book
Grokking Artificial Intelligence Algorithms uses illustrations, exercises, and jargon-free explanations to teach fundamental AI concepts. All you need is the algebra you remember from high school math class. Explore coding challenges like detecting bank fraud, creating artistic masterpieces, and setting a self-driving car in motion.
What's inside
Use cases for different AI algorithms
Intelligent search for decision making
Biologically inspired algorithms
Machine learning and neural networks
Reinforcement learning to build a better robot
About the reader
For software developers with high school–level algebra and calculus skills.
About the author
Rishal Hurbans is a technologist, startup and AI group founder, and international speaker.
Table of Contents
1 Intuition of artificial intelligence
2 Search fundamentals
3 Intelligent search
4 Evolutionary algorithms
5 Advanced evolutionary approaches
6 Swarm intelligence: Ants
7 Swarm intelligence: Particles
8 Machine learning
9 Artificial neural networks
10 Reinforcement learning with Q-learning
Summary
Grokking Artificial Intelligence Algorithms is a fully-illustrated and interactive tutorial guide to the different approaches and algorithms that underpin AI. Written in simple language and with lots of visual references and hands-on examples, you’ll learn the concepts, terminology, and theory you need to effectively incorporate AI algorithms into your applications. And to make sure you truly grok as you go, you’ll use each algorithm in practice with creative coding exercises—including building a maze puzzle game, performing diamond data analysis, and even exploring drone material optimization.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
About the technology
Artificial intelligence touches every part of our lives. It powers our shopping and TV recommendations; it informs our medical diagnoses. Embracing this new world means mastering the core algorithms at the heart of AI.
About the book
Grokking Artificial Intelligence Algorithms uses illustrations, exercises, and jargon-free explanations to teach fundamental AI concepts. All you need is the algebra you remember from high school math class. Explore coding challenges like detecting bank fraud, creating artistic masterpieces, and setting a self-driving car in motion.
What's inside
Use cases for different AI algorithms
Intelligent search for decision making
Biologically inspired algorithms
Machine learning and neural networks
Reinforcement learning to build a better robot
About the reader
For software developers with high school–level algebra and calculus skills.
About the author
Rishal Hurbans is a technologist, startup and AI group founder, and international speaker.
Table of Contents
1 Intuition of artificial intelligence
2 Search fundamentals
3 Intelligent search
4 Evolutionary algorithms
5 Advanced evolutionary approaches
6 Swarm intelligence: Ants
7 Swarm intelligence: Particles
8 Machine learning
9 Artificial neural networks
10 Reinforcement learning with Q-learning