Foundational CS for ML Engineers
The computer science foundations that make ML engineers dangerous - CPU and GPU architecture, operating systems, compilers, memory management, networking, algorithms, and systems programming.
2 docs tagged with "systems"
View all tagsHardware and Silicon for AI
GPU architecture, CUDA programming, custom silicon, kernel optimization, memory systems, and distributed training hardware - the layer below the framework that determines what is actually possible.