Deep Learning Cheat Sheet for Beginners

Deep Learning Cheat Sheet for Beginners


This article was written by  Ian Goodfellow, Yoshua Bengio, and Aaron Courville. It consists of summaries, dozens of formulas, and numerous small sections that will help the beginner quickly grasp the essentials of deeplearning. The presentation style is very similar to a cheat sheet

Example of bad data science: over-fitting
Content:

Machine Learning
Generalization and Overfitting
Feedforward Networks
Designing the Output Layer
Finding θ
Choosing the Cost Function
Regularization
Deep Feedforward Networks
Designing Hidden Layers
Optimizaton Methods
Simplifying the Network
Convolution Networks
Pooling
Recurrent Networks
Useful Data Sets
Autoencoders
Representation Learning
Practical Advice
Appendix: Probability

To read the full original article click here. For more deep learning related articles on DSC click here.
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Link: Deep Learning Cheat Sheet for Beginners