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Machine Learning from Zero

Classical machine learning

1. What is machine learning?
2. The taxonomy of machine learning paradigms
3. Linear regression
4. Logistic regression
5. Building the machine learning interface
6. Entering higher dimensions

Neural networks

7. Computational graphs
8. Training neural networks
9. The forward pass
10. The backward pass (in theory)
11. The backward pass (in practice)
12. Optimizing with gradient descent
13. Vectorized computational graphs
14. Vectorizing backpropagation (in theory)
15. Vectorizing backpropagation (in practice)

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By Tivadar Danka

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