Über dieses Buch
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.
Regularization Techniques to Improve Generalization
Improving Network Models and Algorithmic Tricks
Representing and Incorporating Prior Knowledge in Neural Network Training
Tricks for Time Series
Big Learning in Deep Neural Networks
Better Representations: Invariant, Disentangled and Reusable
Identifying Dynamical Systems for Forecasting and Control
- Neural Networks: Tricks of the Trade
- Springer Berlin Heidelberg
- Print ISBN
- Electronic ISBN
Geneviève B. Orr