Lab 7: Paragraph Recognition (Full Stack Deep Learning - Spring 2021)

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Full-course playlist 'Full Stack Deep Learning - Spring 2021' from a curated course list (Full Stack Deep Learning - Course 2021); uploader is instructor; playlist judged: A full, substantive UC Berkeley deep learning course with lectures and hands-on labs uploaded by the instructors' own channel.; title passed a strict title check; oEmbed verified.

What you'll learn

A 19-minute video from The Full Stack: “Lab 7: Paragraph Recognition (Full Stack Deep Learning - Spring 2021)”.

Programming & CS

Video by The Full Stack, played through YouTube's embedded player.

8:37

Lab 02: PyTorch Lightning and Convolutional NNs (FSDL 2022)The Full StackProgramming & CS

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Lecture 4: Transfer Learning and Transformers (Full Stack Deep Learning - Spring 2021)The Full StackProgramming & CS

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

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The spelled-out intro to neural networks and backpropagation: building micrograd Andrej KarpathyProgramming & CS

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24:26

The Beauty of Bézier Curves Freya HolmérProgramming & CS

2.23M views

2:27:41

CS50x 2024 - Lecture 1 - C CS50Programming & CS

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

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

65.7K views

2:04:55

CS50x 2024 - Lecture 0 - Scratch CS50Programming & CS

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RailsConf 2014 - All the Little Things by Sandi Metz ConfreaksProgramming & CS

190K views

8:37

Lab 02: PyTorch Lightning and Convolutional NNs (FSDL 2022)

The Full Stack

A 9-minute video from The Full Stack: “Lab 02: PyTorch Lightning and Convolutional NNs (FSDL 2022)”.

48:30

Lecture 4: Transfer Learning and Transformers (Full Stack Deep Learning - Spring 2021)

The Full Stack

A 48-minute video from The Full Stack: “Lecture 4: Transfer Learning and Transformers (Full Stack Deep Learning - Spring 2021)”.

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

8.21M views

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

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.

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.

24:26

The Beauty of Bézier Curves

Freya Holmér

2.23M views

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

Intro1.41M views

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

“Hello, world” from scratch on a 6502 — Part 1

Ben Eater

5.85M views

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

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

Confreaks

65.7K views

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.

2:04:55

CS50x 2024 - Lecture 0 - Scratch

CS50

Intro2.2M views

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

RailsConf 2014 - All the Little Things by Sandi Metz

Confreaks

190K views

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.