// The Library
Technical Deep Dives,
& systems logic.
Consult the index...
⌘K
Latest Updates
3. Maths4ML: Dot Product
Shadows, Angles, and the Geometry of Sameness
›
2. Maths4ML: Distances & Norms
Measuring the gap - Rulers of ML
›
1. Maths4ML: Vectors, Basis & Spans
The Building Blocks – Vectors, Basis & Spans
›
11. NLP: Tokenizers
A detailed description about tokenizers in LLMs.
›
10. NLP: Mixture of Experts (MOE)
A guide on MoEs, their history and implementation in transformers along with the losses associated with it.
›
9. NLP: Optimizing Attention
A guide on KV-Caching along with Sliding Window Attention. Ending with MQA and GQA.
›
8. NLP: BERT
A guide on BERT models and how their architecture.
›
7. NLP: Transformer Implementation
Implementation and trainig of Transformer for En-Hi machine translation task.
›
4. NLP: Seq2Seq
A guide on Seq2Seq models that changed machine translation task.
›
3. NLP: Pytorch for NLP
Some tips for working with PyTorch for NLP tasks
›