Tim Gates
e40f51f267
There are small typos in: - code/ch01/README.md - code/ch12/optional-streamlined-neuralnet.py - faq/ai-and-ml.md - faq/naive-bayes-vartypes.md - faq/scale-training-test.md Fixes: - Should read `were` rather than `weere`. - Should read `occurrences` rather than `occurences`. - Should read `laborious` rather than `labrorious`. - Should read `initializing` rather than `initalizing`. - Should read `distribution` rather than `distribtion`. - Should read `dataset` rather than `datast`.
Sebastian Raschka, 2015
Python Machine Learning - Code Examples
Chapter 12 - Training Artificial Neural Networks for Image
- Modeling complex functions with artificial neural networks
- Single-layer neural network recap
- Introducing the multi-layer neural network architecture
- Activating a neural network via forward propagation
- Classifying handwritten digits
- Obtaining the MNIST dataset
- Implementing a multi-layer perceptron
- Training an artificial neural network
- Computing the logistic cost function
- Training neural networks via backpropagation
- Developing your intuition for backpropagation
- Debugging neural networks with gradient checking
- Convergence in neural networks
- Other neural network architectures
- Convolutional Neural Networks
- Recurrent Neural Networks
- A few last words about neural network implementation
- Summary