| Ressource | Link |
|---|---|
| [Book] - Pattern Recognition and Machine Learning by Bishop | [Open] |
| [Book] - The Elements of Statistical Learning | [Open] |
| [Book] - Designing Machine Learning Systems: An Iterative Process for Production-Ready Application | [Open] |
| [Blog] - Why model calibration matters and how to achieve it | [Open] |
| [Blog] - A Recipe for Training Neural Networks by Andrej Karpathy | [Open] |
| [Blog] - Reservoir Sampling by Florian Hartmann | [Open] |
| [Website] - Use the index, Luke ! | [Open] |
| [Book] - Algorithms by Jeff Erickson | [Open] |
| [Book] - Web Scraping with Python: Data Extraction from the Modern Web | [Open] |
| [Book] - Information Theory: A Tutorial Introduction | [Open] |
| [Website] - Learn X in Y minutes | [Open] |
| [Book] - Learn Docker in a Month of Lunches | [Open] |
| [Book] - Minning the social web | [Open] |
|
[
] - Diffusion Models Are Real-Time Game Engines
|
[Open] |
| [Algorithm] - Fast Algorithms for Convolutional Neural Network | [Open] |
| [Guide] - Step-by-Step Diffusion: An Elementary Tutorial | [Open] |
| [Paper] - The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits | [Open] |
| [GitHub] - bitnet.cpp | [Open] |
| [Paper] - An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale | [Open] |
| [Paper] - An Image is Worth More Than 16x16 Patches: Exploring Transformers on Individual Pixels | [Open] |
| [Paper] - Video PreTraining (VPT): Learning to Act by Watching Unlabeled Online Videos | [Open] |
| [Guide] - Step-by-Step Diffusion: An Elementary Tutorial | [Open] |
| [Guide] - Neural Machine Translation and Sequence-to-sequence Models: A Tutorial | [Open] |
| [Guide] - Practical recommendations for gradient-based training of deep architectures | [Open] |
| [Guide] - The Ultimate Guide to Fine-Tuning LLMs from Basics to Breakthroughs | [Open] |