Machine Learning Systems — Introduction

I'm finally getting around to posting writing of mine related to machine learning systems (geared towards deep learning). I've organized this into a series of technical posts, emphasizing both accessibility and depth.

The series, as it grows can be found here.

These articles are organized into the following high-level categories:

1. Mathematical foundations — treatments of tensors, automatic differentiation and backpropagation.
2. GPUs — technical underpinnings of the architecture of GPUs as motivated by parallel computation.
3. Distributed systems and performance — analysis of bottlenecks and intuition around large-scale systems.
4. Building — architecture and implementation knowledge around building real systems.

This will be a living, breathing collection that I'll add to and fix errata in over time.

Citation

@misc{kahn2024mlsystems,
  title        = {Machine Learning Systems},
  author       = {Jacob Kahn},
  year         = {2024},
  url          = {https://jacobkahn.me/writing/tag/machine_learning_systems/},
}