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Neural Networks for Electronics Hobbyists: A Non-Technical Project-Based Introduction
Neural Networks for Electronics Hobbyists: A Non-Technical Project-Based Introduction
Learn how to implement and build a neural network with this non-technical, project-based book as your guide. As you work through the chapters, you'll build an electronics project, providing a hands-on experience in training a network. 

There are no prerequisites here and you won't see a single line of
...
An Introduction to Genetic Algorithms (Complex Adaptive Systems)
An Introduction to Genetic Algorithms (Complex Adaptive Systems)

Science arises from the very human desire to understand and control the world. Over the course of history, we
humans have gradually built up a grand edifice of knowledge that enables us to predict, to varying extents, the
weather, the motions of the planets, solar and lunar eclipses, the courses of diseases, the rise and fall
...

Computational Intelligence: Principles, Techniques and Applications
Computational Intelligence: Principles, Techniques and Applications
Computational Intelligence: Principles, Techniques and Applications presents both theories and applications of computational intelligence in a clear, precise and highly comprehensive style. The textbook addresses the fundamental aspects of fuzzy sets and logic, neural networks, evolutionary computing and belief networks. The...
Artificial Intelligence By Example: Develop machine intelligence from scratch using real artificial intelligence use cases
Artificial Intelligence By Example: Develop machine intelligence from scratch using real artificial intelligence use cases

Be an adaptive thinker that leads the way to Artificial Intelligence

Key Features

  • AI-based examples to guide you in designing and implementing machine intelligence
  • Develop your own method for future AI solutions
  • Acquire advanced AI, machine learning, and...
Pattern Recognition with Neural Networks in C++
Pattern Recognition with Neural Networks in C++

Why do we feel a need to write a book about pattern recognition when many excellent books are already available on this classical topic? The answer lies in the depth of our coverage of neural networks as natural pattern classifiers and clusterers. Artificial neural network computing has emerged as an extremely active research area with a central...

Computational Intelligence: Methods and Techniques
Computational Intelligence: Methods and Techniques
This book focuses on various techniques of computational intelligence, both single ones and those which form hybrid methods. Those techniques are today commonly applied issues of artificial intelligence, e.g. to process speech and natural language, build expert systems and robots. The first part of the book presents methods of knowledge...
Simulated Annealing and Boltzmann Machines: A Stochastic Approach to Combinatorial Optimization and Neural Computing
Simulated Annealing and Boltzmann Machines: A Stochastic Approach to Combinatorial Optimization and Neural Computing

Wiley-Interscience Series in Discrete Mathematics and Optimization Advisory Editors Ronald L. Graham Jan Karel Lenstra Robert E. Tarjan Discrete Mathematics and Optimization involves the study of finite structures. It is one of the fastest growing areas in mathematics today. The level and depth of recent advances in the area and the wide...

Advanced Intelligent Computational Technologies and Decision Support Systems (Studies in Computational Intelligence)
Advanced Intelligent Computational Technologies and Decision Support Systems (Studies in Computational Intelligence)

This book offers a state of the art collection covering themes related to Advanced Intelligent Computational Technologies and Decision Support Systems which can be applied to fields like healthcare assisting the humans in solving problems. The book brings forward a wealth of ideas, algorithms and case studies in themes like:...

Neural Networks in Unity: C# Programming for Windows 10
Neural Networks in Unity: C# Programming for Windows 10
Learn the core concepts of neural networks and discover the different types of neural network, using Unity as your platform. In this book you will start by exploring back propagation and unsupervised neural networks with Unity and C#. You’ll then move onto activation functions, such as sigmoid...
An Introduction to Neural Networks
An Introduction to Neural Networks
Covers: artificial neurons as models of their real counterparts; the geometry of network action in pattern space; gradient descent methods, including back-propagation; associative memory and Hopfield nets; and self-organization and feature maps.

This book grew out of a set of course notes for a neural networks module given as part of a
...
Gamification by Design: Implementing Game Mechanics in Web and Mobile Apps
Gamification by Design: Implementing Game Mechanics in Web and Mobile Apps

Gamification may be a new term, but the idea of using game-thinking and game mechanics to solve problems and engage audiences isn’t exactly new. The military has been using games and simulations for hundreds (if not thousands) of years, and the U.S. military has been a pioneer in the use of video games across branches. Three...

Thoughtful Machine Learning: A Test-Driven Approach
Thoughtful Machine Learning: A Test-Driven Approach

Learn how to apply test-driven development (TDD) to machine-learning algorithms—and catch mistakes that could sink your analysis. In this practical guide, author Matthew Kirk takes you through the principles of TDD and machine learning, and shows you how to apply TDD to several machine-learning algorithms, including Naive...

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