Your portal into the world of neural networks
353491
Several previous commenters have praised Jeff on his concise writing style and how he conveys a complex topic in an easily digestible manner. Let me put it another way - about a week ago I knew almost nothing about Artificial Neural Networks. My math skills are pretty decent (I'm a programmer) but I'm not versed in calculus. Now, I'm only half way through the book and it already has managed to give me a running start on all the basic concepts involved in building and training ANNs. I'm able to read pertinent white papers now plastered with formulas which largely escape me - but I am able to grasp the underlying principles and overall idea. I wouldn't be able to fully explain to you how resilient back propagation works, however the basic concept behind is now clear to me. I am also able to differentiate between various propagation training techniques and when to choose what type of data normalization. And that is sufficient in order to get started with experimenting and training simple ANNs. But the icing on the cake for me was that Jeff is offering a downloadable API and workbench (Encog) on his website for FREE. Plus there are ample examples in the book, providing hands-on examples and training. This is not just a technical book - it's a guided journey offering non-mathematicians the opportunity to explore the exotic world of neural networks. Which is why I believe it deserved a five-star rating. The book should be called 'Everything You Always Wanted To Know About Neural Nets, And Never Dared To Ask'.
2075114
THIS IS A GREAT IDEA and while it was hard for me to really get a grip on the technical jargon, I enjoyed reading it and commend Dr.(??) Gregory Bernes for advancing into this particular field of neuroscience. Will look forward to learning more of what he learns.
2797553
The books succeeds in elucidates the complex world of fMRI statistics. The book guides a reader throughout the process of fMRI data analysis with clear, practical examples. It is also possible to read select chapters on particular topics of interest. Additionally, there are many specific tips and tricks to improve the quality of fMRI studies and subsequent analysis. The value (i.e., price for information) is extraordinary. Thus, making it an appropriate textbook choice for a graduate level course in fMRI data analysis. As additional value, there is Matlab code on his personal website, [...], to facilitate a deeper understanding of the concepts. Overall, this book is an invaluable asset to the field.
3230250
Great introduction to neural networks in an easy to understand way. The sections were clearly labeled and detailed explanations for the code were provided. Additionally, the program is constructed in such a way that it can be easily modified for many scenarios beyond the given exclusive OR problem.
3292144
An excellent book: Each chapter is explained very well and it is readable and understandable.
It covers a lot of modern advances, e.g. deep learning.
It is the best machine learning book that I currently own.
1127949
This book outlines many implementation questions you will come across in your organization and looks well in to strategy. For someone looking to start using mLearning in a thoughtful way, this is a guiding light that should not be ignored. In this book the author dives in to a number of very deep concepts in how to design for future learning situations. These are not always easy, but well worth taking in.
3532312
This is the first book that has clearly broken down backpropagation in a way that is easy to follow and understand. It's has been around 15 years since I've taken a math class. By trade I'm a developer and this is something I've been wanting and needing to learn for sometime now.

Michael Taylor does an excellent job breaking down exactly how neural networks work.
4853933
Web 2.0 is everywhere.  When you log into Amazon or Netflix or del.icio.us  you'll see sites that know a lot about you and can recommend choices based on past history.  The machinery for accomplishing this is nicely laid out in "Programming Collective Intelligence".  The math isn't strenuous, but the implications can be profound.

My preference might have been to see examples written in Java, but I've come to appreciate the author's choice of Python.  It's been a good motivator for exposing myself to a new language.  The code has the virtue of being succinct.  I've seen ports to Scheme and JavaScript on the web.

The book is generating some fair buzz.  I recommend it highly.
3437268
This is a very nice interdisciplinary book. It deals with neuronal models and a number of issues related to filtering and  model uncertainty. This book will prove helpful for those who need to grasp knowledge about neurons, models and data from both. There is much information on historical development of the field which is an extra benefit. The author succeeds in making a strong point for Kalman filtering (in one of its nonlinear versions, the UKF) as a tool for handling, model, data and uncertainty. The book, which is very well written, reads more like a research monograph than a textbook and the bias is clearly towards neural issues albeit the author's efforts to relate the material to control engineering. Given the "plant" considered by the author, it is fair to say that his efforts have been quite successful.
464919
The smallest and most important unit of the artificial neural network is the neuron. As in biological neural systems, these neurons are connected with each other and together, they have the great processing power.

The author makes very easy to understand how the build a computer neuron. I badly needed a book which can give me perfect solution to know the core of neural networks. How to train a Neural network this part of this made me interested.

Recommended!!!
4099899
Joel has a way of MAKING IDEAS available for connection in many neural pathways!
4890740
It's an accessible treatment of several machine learning algorithms. Some of the examples are good scaffolds for future projects.
651307
Make Your Own Neural Network was a very informative guide that explained how AI works as well as how email filters work to block out spam. There were also diagrams and the steps and formulas were explained in an easy to understand way. Each step was thoroughly explained and you can tell that great care was taken in writing this book.

I read this book because I enjoy learning new things and being able to implement them in my life. Its easy to see that Michael had beginners in mind which was appreciated.

Some of the information was over my head because math and science admittedly are not some of my stronger suits. It also talks about algorithms that we are used to seeing on social media websites like Instagram and Facebook.
3430972
This work, ..., is very useful to those of us who are setting up trading systems based on Neural Nets or using other Cybernetic techniques. Yes the writing style may not be the best, but this does not take away from the high quality of the technical material, which is what is really important.
Mr Jurik has some very interesting Low-Lag technical indicators available on his web site....
If you are attempting to design a profitable trading system which uses technical analysis for Stock or Futures trading, this book should be on your shelf.
821641
In the book, Decision Trees and Random Forests: A Visual Introduction For Beginners: A Simple Guide to Machine Learning with Decision Trees, the author Chris Smith makes the complicated, simple. Decision tree and random forest algorithms are often used throughout business to more quickly assimilate information and make it more accessible. These algorithms work seamlessly behind the scenes in industries from credit scoring to product development. With the use of easy to understand drawings, Chris Smith puts together a comprehensive look at how to use these applications to your advantage whether in business or even in your personal life. His example of the ice cream shop, and whether or not the shop should move to a different location is a great tutorial that explains in layman's terms how decision trees work at a very fundamental level. A great visual guide with clear illustrations, this book is strongly recommended for the beginner in machine learning algorithms in Python.
4033647
Some knowledge of C++ is essential, but classes are very well laid out, and code is easy to use and re-use.  To an extent, it is too academic, and could be streamlined a bit for performance. More comprehensive examples  would be a plus.  Overall an excellent introduction to neural net  programming. A follow-up on other neural net architectures would be greatly  appreciated.
1319545
Micheal Taylor has done a good job with researching and discussing that research in an easy to follow and understand method. There were a couple of times when I had to read a section twice but the overall collection and presentation of the material is very good. If you are interested in the neural network and how it works and learns , this is a good place to start.