Books

AlgebraCalculusLinear Algebra

I write textbooks for fun as a way to consolidate and clarify my quantitative intuition. The goal is to provide deep intuition for the core concepts and connections, along with plenty of practice exercises, while remaining as concise as possible.

Algebra

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Calculus

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Linear Algebra

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Introductory Exercises in Computation

In progress

Classical Supervised Machine Learning

In progress

Neural Networks

To be written!
  • 1. Neural Networks - Architecture, Initialization, and Data Normalization in Neural Networks; Computing Weight Gradients via Chain Rule; Computing Weight Gradients via Path Enumeration; Computing Weight Gradients via Backpropagation; Evolving Weights in Neural Networks; Data Augmentation and Adversarial Examples; Dropout and Batch Normalization.
  • 2. Convolutional Neural Networks - Convolutional and Pooling Layers; ...
  • 3. Applications of Convolutional Neural Networks - Object Localization; Deep Dream; Neural Style Transfer; Deepfakes; Blondie24; ...
  • 4. Recurrent Neural Networks - Long Short-Term Memory Units; Backpropagtion Through Time; ...
  • 5. Applications of Recurrent Neural Networks - Text Summarization; Image Captioning; Translation; Chatbots; ...