KUEE, KECE-207) Deep Learning in Digital Systems Part 3

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What you'll learn

A 36-minute video from Joongheon Kim: “KUEE, KECE-207) Deep Learning in Digital Systems Part 3”.

Programming & CS

Video by Joongheon Kim, played through YouTube's embedded player.

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딥러닝기초프로그래밍) GAN, 인공신경망과 function approximation, PCA/LDA, overfitting

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A 76-minute video from Joongheon Kim: “딥러닝기초프로그래밍) GAN, 인공신경망과 function approximation, PCA/LDA, overfitting”.

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Builds up what a neural network actually is — neurons as numbers, layers, weights and biases — using handwritten-digit recognition as the running example.

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Building a GPT-style language model from scratch in code, following 'Attention Is All You Need'.

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How transformer models (the 'T' in GPT) turn text into vectors and predict the next token, step by step.

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Building micrograd, a tiny autograd engine, to understand backpropagation completely.

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Freya Holmér builds Bézier curves from linear interpolation up, covering de Casteljau's algorithm, derivatives, arc length and their use in games and graphics.

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Building a computer around the 6502 processor on a breadboard and running 'Hello, world'.

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Sandi Metz refactors the notorious Gilded Rose kata live, showing how small, disciplined steps and duplication-over-wrong-abstraction lead to clean object-oriented code.