Archive: Interactive Data Analysis

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Hand-picked by a BrighterTube curator · found via round-3 back catalogue of a channel Lumen picks video by video · 82% confidence

Teaches interactive data analysis methods and tools. Data science instruction on analysis techniques and visualization.

A 28-minute video from UW Video: “Archive: Interactive Data Analysis”.

Programming & CS

Video by UW Video, played through YouTube's embedded player.

Part of 2013 Computer Science & Engineering Colloquia

1:02:38

Archive: Art-Based Modeling for Computer Graphics UW VideoArt & Design

But what is a neural network? | Deep learning chapter 1 3Blue1BrownScience & Math

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Let's build GPT: from scratch, in code, spelled out.Andrej KarpathyProgramming & CS

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Transformers, the tech behind LLMs | Deep Learning Chapter 5 3Blue1BrownProgramming & CS

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The Beauty of Bézier Curves Freya HolmérProgramming & CS

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CS50x 2024 - Lecture 1 - C CS50Programming & CS

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Ruby Conf 12 - Y Not- Adventures in Functional Programming by Jim Weirich ConfreaksProgramming & CS

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“Hello, world” from scratch on a 6502 — Part 1 Ben EaterProgramming & CS

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CS50x 2024 - Lecture 0 - Scratch CS50Programming & CS

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The Continuity of Splines Freya HolmérProgramming & CS

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The Most Underrated Algorithm VeritasiumProgramming & CS

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Archive: Art-Based Modeling for Computer Graphics

UW Video

A 63-minute video from UW Video: “Archive: Art-Based Modeling for Computer Graphics”.

But what is a neural network? | Deep learning chapter 1

3Blue1Brown

Intro25.1M views

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

Let's build GPT: from scratch, in code, spelled out.

Andrej Karpathy

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

The spelled-out intro to neural networks and backpropagation: building micrograd

Andrej Karpathy

Intro4.41M views

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

Transformers, the tech behind LLMs | Deep Learning Chapter 5

3Blue1Brown

Intro11.6M views

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

24:26

The Beauty of Bézier Curves

Freya Holmér

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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.

2:27:41

CS50x 2024 - Lecture 1 - C

CS50

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CS50x 2024 lecture 1: an introduction to C — syntax, types, conditionals, loops and compiling.

Ruby Conf 12 - Y Not- Adventures in Functional Programming by Jim Weirich

Confreaks

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Jim Weirich derives the Y combinator live, step by step, using nothing but Ruby lambdas, and along the way teaches the refactorings of lambda calculus.

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Ben Eater

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

2:04:55

CS50x 2024 - Lecture 0 - Scratch

CS50

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CS50x 2024 lecture 0: how computers represent information, algorithms, and first programs in Scratch.

1:13:50

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A follow-up on splines: the different kinds of continuity (C and G), and how Hermite, Catmull-Rom, B-splines and NURBS trade them off.

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Veritasium

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The history and inner workings of the Fast Fourier Transform, from nuclear test detection to everyday signal processing.