AI by Hand ✍️

AI by Hand ✍️

Matrix Multiplication by Hand ✍️

Calculating AI by Hand: 1 of 28

Prof. Tom Yeh's avatar
Prof. Tom Yeh
Jan 05, 2024
∙ Paid

Library › Calculating AI by Hand ✍️

  1. Matrix Multiplication by Hand ✍️

  2. Multi Layer Perceptron (MLP) by Hand ✍️

  3. Backpropagation by Hand ✍️

  4. SVM by Hand ✍️

  5. Batch Normalization by Hand ✍️

  6. Dropout by Hand ✍️

  7. Recurrent Neural Network (RNN) by Hand ✍️

  8. LSTM by Hand ✍️

  9. Deep RNN by Hand ✍️

  10. Self Attention by Hand ✍️

  11. Transformer by Hand ✍️

  12. Autoencoder by Hand ✍️

  13. Variational Auto Encoder (VAE) by Hand ✍️

  14. Sparse Auto Encoder (SAE) by Hand ✍️

  15. Generative Adversarial Network (GAN) by Hand ✍️

  16. Sampling a Sentence by Hand ✍️

  17. Residual Network by Hand ✍️

  18. U-Net by Hand ✍️

  19. Discrete Fourier Transform by Hand ✍️

  20. Graph Convolutional Network (GCN) by Hand ✍️

  21. CLIP by Hand ✍️

  22. Vector Database by Hand ✍️

  23. Mixture of Experts (MoE) by Hand ✍️

  24. Switch Transformer by Hand ✍️

  25. Mamba's S6 by Hand ✍️

  26. Sora's Diffusion Transformer (DiT) by Hand ✍️

  27. BitNet by Hand ✍️

  28. Reinforcement Learning with Human Feedback (RLHF) by Hand ✍️

One of the key ingredients of the deep learning revolution is the ability to perform matrix multiplications at incredible speed and scale.

Despite linear algebra being a prerequisite of my courses, I found many students lack confidence in multiplying matrices. So I teach them this unique system for multiplying matrices by hand.

How does it work?

Setup

Step 1 of 9: Given

  • Multiply A (green, 2×2) by B (yellow, 2×3).

  • Lay them out compactly: B across the top, A down the left, and an empty grid for the result C where they meet.

Lay Out the Matrices

Step 2 of 9: Place B

  • Copy B's values across the top.


Step 3 of 9: Place A

  • Copy A's values down the left.

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