Lecture 35 - Visualizing loss landscapes - BYU CS 474 Deep Learning

Why it's on BrighterTube

Editorial review · 85% confidence

Round-16 hunt: picked; source: course-code search in local formats (r16); channel screens (sellers/exam/re-upload/devotional/vendor/events), provenance check, vendor/seller/devotional recheck and quality tier B passed; strict per-title check + final strict pass; oEmbed verified.

What you'll learn

A 44-minute video from Jacob Stern: “Lecture 35 - Visualizing loss landscapes - BYU CS 474 Deep Learning”.

Programming & CS

Video by Jacob Stern, played through YouTube's embedded player.

47:21

Lecture 12 - Style Transfer - BYU CS 474 Deep Learning Jacob SternProgramming & CS

47:39

Lecture 16 - Recurrent neural networks (continued) - BYU CS 474 Deep Learning Jacob SternProgramming & CS

But what is a neural network? | Deep learning chapter 1 3Blue1BrownScience & Math25.1M views

Let's build GPT: from scratch, in code, spelled out.Andrej KarpathyProgramming & CS8.21M views

Transformers, the tech behind LLMs | Deep Learning Chapter 5 3Blue1BrownProgramming & CS11.6M views

The spelled-out intro to neural networks and backpropagation: building micrograd Andrej KarpathyProgramming & CS4.41M views

24:26

The Beauty of Bézier Curves Freya HolmérProgramming & CS2.23M views

2:27:41

CS50x 2024 - Lecture 1 - C CS50Programming & CS1.41M views

15:51

How semiconductors work Ben EaterEngineering488K views

“Hello, world” from scratch on a 6502 — Part 1 Ben EaterProgramming & CS5.85M views

Ruby Conf 12 - Y Not- Adventures in Functional Programming by Jim Weirich ConfreaksProgramming & CS65.7K views

2:04:55

CS50x 2024 - Lecture 0 - Scratch CS50Programming & CS2.2M views

47:21

Lecture 12 - Style Transfer - BYU CS 474 Deep Learning

Jacob Stern

A 47-minute video from Jacob Stern: “Lecture 12 - Style Transfer - BYU CS 474 Deep Learning”.

47:39

Lecture 16 - Recurrent neural networks (continued) - BYU CS 474 Deep Learning

Jacob Stern

A 48-minute video from Jacob Stern: “Lecture 16 - Recurrent neural networks (continued) - BYU CS 474 Deep Learning”.

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

3Blue1Brown25.1M 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 Karpathy8.21M 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

3Blue1Brown11.6M 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 Karpathy4.41M views

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

24:26

The Beauty of Bézier Curves

Freya Holmér2.23M 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

CS501.41M views

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

15:51

2:04:55

CS50x 2024 - Lecture 0 - Scratch

CS502.2M views

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