Difference between revisions of "AI tutorials"
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==Loss Functions== | ==Loss Functions== | ||
* [https://gombru.github.io/2018/05/23/cross_entropy_loss/ Understanding Categorical Cross-Entropy Loss, Binary Cross-Entropy Loss, Softmax Loss, Logistic Loss, Focal Loss and all those confusing names] | * [https://gombru.github.io/2018/05/23/cross_entropy_loss/ Understanding Categorical Cross-Entropy Loss, Binary Cross-Entropy Loss, Softmax Loss, Logistic Loss, Focal Loss and all those confusing names] | ||
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| + | ==Diffusion== | ||
| + | * 2024-06: [https://arxiv.org/abs/2406.08929 Step-by-Step Diffusion: An Elementary Tutorial] | ||
==Transformer== | ==Transformer== | ||
Latest revision as of 08:29, 10 July 2025
Contents
General
- MLU-EXPLAIN
- Deep Learning is Not So Mysterious or Different
- AI Digest: Interactive AI explainers
- OpenAI Academy
- Evolution of LLMs
Loss Functions
Diffusion
Transformer
- Low-level:
- Wolfram: What Is ChatGPT Doing … and Why Does It Work?
- The Illustrated Transformer
- Transformers Explained Visually — Not Just How, but Why They Work So Well
- Understanding Positional Encoding in Transformers
Visualizations
LLM
- Toy Models of Superposition
- A Survey on Large Language Models: Applications, Challenges, Limitations, and Practical Usage
- Aman AI: Overview of Large Language Models
- Awesome-LLM: Curated list of LLM projects
- The Big Book of Large Language Models (Damien Benveniste)
- 2025-01: Foundations of Large Language Models
Video
- Andrej Karpathy:
Prompt Engineering
- 2025-04: Lee Boonstra (Google): Prompt Engineering
