Deep-dive articles on machine learning, AI engineering, and production ML systems
A step-by-step implementation of the original Attention is All You Need architecture — multi-head attention, positional encoding, encoder-decoder stack.
Mixed precision, gradient checkpointing, DataLoader tuning, torch.compile, and 6 more tricks with measured speedups on real experiments.
GPU utilization, bottleneck diagnosis, DataLoader optimization, and CUDA memory management — practical techniques for training 2x faster without new hardware.
I build custom ML models, AI agents, computer vision, and automation — from idea to production.