Description
Christopher M.Bishop – Neural Networks for Pattern Recognition
This is the first comprehensive treatment of feed-forward neural networks from the perspective of statistical pattern recognition. After introducing the basic concepts, the book examines techniques for modeling probability density functions and the properties and merits of the multi-layer perceptron and radial basis function network models. Also covered are various forms of error functions, principal algorithms for error function minimalization, learning and generalization in neural networks, and Bayesian techniques and their applications. Designed as a text, with over 100 exercises, this fully up-to-date work will benefit anyone involved in the fields of neural computation and pattern recognition.
Christopher M.Bishop, Neural Networks for Pattern Recognition, Download Neural Networks for Pattern Recognition, Free Neural Networks for Pattern Recognition, Neural Networks for Pattern Recognition Torrent, Neural Networks for Pattern Recognition Review, Neural Networks for Pattern Recognition Groupbuy.


Nigel Da Costa Lewis – Operational Risk with Excel and VBA Applied Statistical Methods for Risk Management
Sergey E.Lyshevski – Engineering & Scientific Computations Using MATLAB
Udemy - Complete Web Development In 1 Bundle!
James C.Spall - Introduction to Stochastic Search and Optimization
Carlos M.Pelaez – The Global Recession Risk
Mark McRae – Traders Secret Library
Tim Cho – Developing a Winning System for Trading High Perfomance Stocks
Raymond Merriman – The Ultimate Book on Stock Market Timing (VOL III) – Geocosmic Correlations to Trading Cycles
Alain Monfort - Simulation-based econometric methods
Glenn J.Myatt, Wayne P.Johnson – Making Sense of Data III – A Practical Guide to Designing Interactive Data Visualizations(HTML)
Joseph L.Fleiss – Statistical Methods for Rates and Proportions

Reviews
There are no reviews yet.