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 essential of deep learning. 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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