Simulating Neural Networks with Mathematica
| Author | : | |
| Rating | : | 4.50 (566 Votes) |
| Asin | : | 020156629X |
| Format Type | : | paperback |
| Number of Pages | : | 352 Pages |
| Publish Date | : | 2017-04-05 |
| Language | : | English |
DESCRIPTION:
Shows how Mathematica can be used to implement and experiment with neural network architectures. Readers will learn how to simulate neural network operations using Mathematica, and will learn techniques for employing Mathematica to assess neural network behavior and performance. Includes Mathematica application programs ("packages") in Appendix. Also for researchers and practitioners interested in using Mathematica as a research tool.Features Teaches the reader about what neural networks are, and how to manipulate them within the Mathematica environment. Addresses a major topic related to neural networks in each chapter, or a specific type of neural network architecture. Contains exercises, suggested projects, and supplementary reading lists with each chapter. For students of neural networks in upper-level undergraduate or beginning graduate courses in computer science, engineering, and related areas. (Also available electronically from Ma
Quite satisfied with the book. Dimwhit Overall, I am quite happy with the book. It does exactly as it describesshows the reader how to use mathematica to simulate several types of Neural Networks. The code is clear, fairly short and the example networks fun to work though. The flexibilty of Mathematica made it a simple task to view what the networks were doing and thus made the networks easier to understand.My only complaint is that the book is too short. Part of this complaint is that I really enjoyed playing with the example nets and hated to see it end. However, only about 8 networks are mentioned and each is covered in 20-30 pagesprogram code included. I wish . A clear way to see how Neural Networks work. A Customer This is another book where the capabilities of Mathematicaare put to good use. Clear explanations and code make it a joy to go through and do all the calculational stuff. Helps even quite experienced people to visualise some of the concepts they may not be experienced with. All the basic models are dealt with. The last chapter on genetic algorithms is a bonus.. No experience needed, all apply This is a great starter for neural networks. It is both a tutorial on neural networks and you write the code as you go.I do not think it matters which version of Mathematica you are using. No previous knowledge is required.This book is structured so that the first few chapters introduce the concepts, and the are various applications. Even the classic Traveling salesperson. The last few chapters are some very specific applied theory. Adaptive Resonance Theory was very interesting.Overall this book is both a fun and educational book.
Readers will learn how to simulate neural network operations using Mathematica and will learn techniques for employing Mathematics to assess neural network behaviour and performance. It shows how this popular and widely available software con be used to explore neural network technology, experiment with various architectures, debug new training algorithms and design techniques for analyzing network performance.. This book introduces neural networks, their operation and their application, in the context of Mathematica, a mathematical programming language