Machine Learning System Resources
Updated
This is my personal list of resources related to machine learning systems. Feel free to drop me an email if you think there’s something worth mentioning. I will try to update this page frequently to include the most recent stuffs in mlsys.
Courses
- 15-884: Machine Learning Systems: offered by Tianqi Chen at CMU.
- CSE 291F: Advanced Data Analytics and ML Systems: offered by Arun Kumar at UCSD.
- Tinyflow: tutorial code on how to build your own Deep Learning System in 2k Lines.
- CSE 599W: Systems for ML: offered by Tianqi Chen at UW.
- CS8803-SMR: Special Topics: Systems for Machine Learning: offered by Alexey Tumanov at Georgia Tech. [schedule]
- CS 744: Big Data Systems: offered by Aditya Akella back at UW-Madison.
- CS 329S: Machine Learning Systems Design: offered by Stanford.
- EECS 598: Systems for AI: offered by Mosharaf Chowdhury at UMich.
- CS 378: Big Data Systems: offered by Aditya Akella at UT.
Labs & Faculties
- CMU Catalyst
- Berkeley RISE Lab
- MIT DASIL Lab
- UW SAMPL
- SymbioticLab
- Shivaram Venkataraman at UW-Madison
- UTNS Lab
- Neeraja Yadwadkar at UT Austin
- SAIL: Systems for Artificial Intelligence Lab @ GT
Tutorials
- Dive into Deep Learning: interactive deep learning book with code, math, and discussions.
- Pytorch-Internals: must-read for PyTorch basics.