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It is our belief that researchers and practitioners acquire, through experience and word-of-mouth, techniques and heuristics that help them successfully apply neural networks to di cult real world problems. Often these ricks" are theo- tically well motivated. Sometimes they are the result of trial and error. However, their most common link is that they are usually hidden in people’s heads or in the back pages of space-constrained conference papers. As a result newcomers to the eld waste much time wondering why their networks train so slowly and perform so poorly. This book is an outgrowth of a 1996 NIPS workshop called Tricks of the Trade whose goal was to begin the process of gathering and documenting these tricks. The interest that the workshop generated motivated us to expand our collection and compile it into this book. Although we have no doubt that there are many tricks we have missed, we hope that what we have included will prove to be useful, particularly to those who are relatively new to the eld. Each chapter contains one or more tricks presented by a given author (or authors). We have attempted to group related chapters into sections, though we recognize that the di erent sections are far from disjoint. Some of the chapters (e.g., 1, 13, 17) contain entire systems of tricks that are far more general than the category they have been placed in.

Neural networks (Computer science) --- Neurale netwerken (Informatica) --- Réseaux neuraux (Informatique) --- Computer Science --- Engineering & Applied Sciences --- Neural networks (Computer science). --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Computer science. --- Microprocessors. --- Computers. --- Artificial intelligence. --- Pattern recognition. --- Complexity, Computational. --- Computer Science. --- Computation by Abstract Devices. --- Artificial Intelligence (incl. Robotics). --- Processor Architectures. --- Pattern Recognition. --- Complexity. --- Artificial intelligence --- Natural computation --- Soft computing --- Optical pattern recognition. --- Engineering. --- Artificial Intelligence. --- Construction --- Industrial arts --- Technology --- Optical data processing --- Pattern perception --- Perceptrons --- Visual discrimination --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Informatics --- Science --- Computational complexity. --- Complexity, Computational --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- Minicomputers --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Cybernetics --- Calculators --- Cyberspace --- Pattern perception.

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The twenty last years have been marked by an increase in available data and computing power. In parallel to this trend, the focus of neural network research and the practice of training neural networks has undergone a number of important changes, for example, use of deep learning machines. The second edition of the book augments the first edition with more tricks, which have resulted from 14 years of theory and experimentation by some of the world's most prominent neural network researchers. These tricks can make a substantial difference (in terms of speed, ease of implementation, and accuracy) when it comes to putting algorithms to work on real problems.

Programming --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer architecture. Operating systems --- Computer Science. --- Computation by Abstract Devices. --- Artificial Intelligence (incl. Robotics). --- Algorithm Analysis and Problem Complexity. --- Pattern Recognition. --- Complexity. --- Information Systems Applications (incl. Internet). --- Computer science. --- Computer software. --- Artificial intelligence. --- Optical pattern recognition. --- Physics. --- Engineering. --- Informatique --- Logiciels --- Intelligence artificielle --- Reconnaissance optique des formes (Informatique) --- Physique --- Ingénierie