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Netlab, by Ian T. Nabney
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Getting the most out of neural networks and related data modelling techniques is the purpose of this book. The text, with the accompanying Netlab toolbox, provides all the necessary tools and knowledge. Throughout, the emphasis is on methods that are relevant to the practical application of neural networks to pattern analysis problems. All parts of the toolbox interact in a coherent way, and implementations and descriptions of standard statistical techniques are provided so that they can be used as benchmarks against which more sophisticated algorithms can be evaluated. Plenty of examples and demonstration programs illustrate the theory and help the reader understand the algorithms and how to apply them.
- Sales Rank: #2031954 in Books
- Brand: Brand: Springer
- Published on: 2004-03-25
- Original language: English
- Number of items: 1
- Dimensions: 9.25" h x 1.00" w x 6.10" l, 1.35 pounds
- Binding: Paperback
- 438 pages
- Used Book in Good Condition
Review
From the reviews:
"...provides a unique collection of many of the most important pattern recognition algorithms. With its use of compact and easily modified MATLAB scripts, the book is ideally suited to both teaching and research."
Christopher Bishop, Microsoft Research, Cambridge, UK
"...a welcome addition to the literature on neural networks and how to train and use them to solve many of the statistical problems that occur in data analysis and data mining."
Jack Cowan, Mathematics Department, University of Chicago, US
"If you have a pattern recognition problem, you should consider NETLAB; if you use NETLAB you must have this book." Keith Worden, University of Sheffield, UK
"Breezing through the elementary algorithms, Nabney takes readers on a tour of the more sophisticated approaches used by real practitioners. ... It is an invaluable resource for the serious student of neural networks."
David S. Touretzky, Computer Science Department, Carnegie Mellon University, US
"Anyone who intends to use Matlab for pattern recognition and related neural computing applications will benefit from this book. It provides a valuable insight into the methods used within the NETLAB toolbox and serves as a useful reference."
Steve King, Strategic Research Centre, Rolls-Royce plc., UK
"The book aims to provide readers with the knowledge and tools to get the most out of neural networks … . A series of worked examples and illustrative demonstration programs are also supplied helping the reader to understand the algorithms … . The book provides an excellent collection of the most important algorithms in pattern recognition. The book can be used as a textbook for teaching undergraduate and postgraduate courses in pattern recognition but it also proves extremely worthy to practitioners and researchers … ." (Luminita State, Zentralblatt MATH, Vol. 1011, 2003)
"In this book, Ian Nabney provides a well-organized description of NETLAB along with plenty of demonstration programs, worked examples and exercises. … Throughout the book, the author strictly follows a uniform style in each chapter. … I think the unification of the style can increase the readability of the book. … The most benefited readers may be the researchers in the same area. Through this book, they can easily find the algorithms they are interested in and use the algorithms for their own purpose." (Lu Zhang, Expert Update, Vol. 5 (3), 2002)
“The book is solely dedicated to explaining the theoretical background of … NETLAB. … mainly presents the algorithms of the functions, their MATLAB program, the formulas used and the required inputs from the users in order to use the functions. … an excellent list of references is included at the end of the book. … useful as an illustrative reference when used with the actual software, but also containing enough scientific explanations and theory to be considered a good reference book alone.” (Eleazar Jimenez Serrano, IAPR Newsletter, January, 2011)
Most helpful customer reviews
3 of 3 people found the following review helpful.
Topnotch
By Gus Harlow
Any praise that I have for this well written, interesting book has already been expressed in other reviews. I do have a couple of observations that may be helpful:
1) This book does not explictly cover everything in Chris Bishop's book. For instance, code for the optimal brain surgeon technique is not covered by Nabney. In fact, several important topics from Chapters 8 and 9 from Bishop are not covered here.
2) Not all of the Matlab code is compatable with Octave, which of course, it doesn't claim to be.
These are not complaints. This is one of the best books on "how to apply software" I've yet to read. But it's not a just a book on algorithms to which it's consise, well placed discussions of theory will attest.
17 of 17 people found the following review helpful.
excellent tools for implementation of P.R. techniques
By A Customer
i first bought the book by Bishop (Neural Network for Pattern Recognition) and anyone who have read it can tell u how excellent that book is. This book has a little bit less theory and more on implementation which is perfect for me. This book include all the topics covered in Bishop and then some. How the book is organized, and how concise, easy to understand the material is at the same amazing level as Bishop's. I believe implementing and practicing things u learn is key to understanding them.. if you just look at how things are implemented, things would suddenly become 10 times clearer for you.. often to your own amazement (that you can actually understand all those stuff). this book is extremely useful even if u dont have matlab (just look up the syntax at mathworks web site), cuz matlab code is straightforward to understand. and the material included is very up to date and cutting edge indeed. i highly highly recommend it.
2 of 2 people found the following review helpful.
Lucid, insightful and completely useful text on Pattern Recognition
By A Reader
Amazingly compact book and MATLAB toolbox that provides an exceptionally clear introduction to a core collection of pattern recognition tools. This text and the related MATLAB toolbox ostensibly accompany Chris Bishop's text _Neural networks for pattern recognition_ and brilliant as that book is, this is the perfect supplement that does so much more than just implement the algorithms (and not just for MATLAB users but for anyone who appreciates the merits of learning by doing). From the introductory chapters on MATLAB syntax and optimization (clearer and more useful than the _Numerical Recipes_ version) you know you are in for a breathless ride but the examples and demos are perfectly chosen to illustrate the relative merits of the different approaches under consideration.
The chapter titles are
1. Introduction
2. Parameter optimisation algorithms
3. Density modelling and clustering
4. Single layer networks
5. Multi-layer perceptron
6. Radial Basis functions
7. Visualization and latent variable models
8. Sampling
9. Bayesian techniques
10. Gaussian Processes
The MATLAB code is elegant and well-commented and lends itself to endless tweaking and experimentation. I wish I had written this book. Congratulations to the author and hope there is another book on the way.
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