IDS - Week 05 - 06 - Doing data science

About this video

From a channel a BrighterTube curator vetted · found via BookPractice list channel (Josh), extended under the whole-channel rule · 80% confidence

From a channel Lumen includes in full: Mine Çetinkaya-Rundel's channel holds her university statistics and data-science course lectures and code-alongs.

A 19-minute video from Mine Çetinkaya-Rundel's catalogue; the title names its topic.

Science & Math Programming & CS

Video by Mine Çetinkaya-Rundel, played through YouTube's embedded player.

Part of Introduction to Data Science

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IDS - Week 08 - 05 - Models with multiple predictors Mine Çetinkaya-RundelScience & Math

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IDS - Week 08 - 05 - Models with multiple predictors

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A 21-minute video from Mine Çetinkaya-Rundel's catalogue; the title names its topic.

20:02

IDS - Week 04 - 05 - Recoding data

Mine Çetinkaya-Rundel

A 20-minute video from Mine Çetinkaya-Rundel's catalogue; the title names its topic.

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

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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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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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Art of the Problem explains Diffie–Hellman key exchange with the paint-mixing analogy and then the modular-arithmetic version.

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Building a fluid simulation step by step with smoothed-particle hydrodynamics.

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Computerphile explains the discrete cosine transform at the heart of JPEG compression.

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