Results for “PyTorch”

Fine-tune, evaluate, serve, monitor. The ML engineer is the person who ships the models that now power medicine, law, and design. It is the highest-leverage engineering role.

Literature reviews, source checking, synthesis, and evidence-aware workflows. 280 lessons.

ML engineers train, fine-tune, and ship the models that power AI products. They're the people who build the tools everyone else in this list uses.

IBM / Coursera — Learners targeting AI engineer roles in under 6 months

Fast.ai — Coders ready to build real deep learning systems fast

CertNexus — Practitioners validating real-world ML skills

PyTorch's Fully Sharded Data Parallel — shards model states across GPUs for memory-efficient training.

A collection of pre-trained models — Hugging Face Hub is the biggest.

Splitting individual matrix multiplies across several GPUs so big layers fit.

DeepSpeed's Zero Redundancy Optimizer — shards optimizer state, grads, and params across GPUs.

Training with both low-precision (BF16/FP16) and high-precision (FP32) numbers where each is best.