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Math for Machine Learning - Exercises: Probability
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- 1 - Teaser
- 2 - Intro
- 3 - Implementing entropies
- 4 - Exercise: surprise
- 5 - Why do models output probabilities?
- 6 - Exercise: entropy
- 7 - Exercise: crossentropy
- 8 - Exercise: divergence
- 9 - Loss functions and surprises
- 10 - Exercise: softmax_crossentropy
- 11 - Putting it all together with Gaussians
- 12 - Exercise: gaussian_surprise
- 13 - Gaussian surprise and squared error
- 14 - Exercise: Gradient descent on a surprise
- 15 - Why are these exercises useful?
- 16 - How programmers can learn more math