Deep Learning

Diagram of a small GPT training loop with mixed precision and gradient accumulation.

Building nanoGPT From Scratch: A Portfolio-Worthy Deep Learning Project

Ship a portfolio-grade nanoGPT implementation in pure PyTorch: a tight training loop with AMP, gradient accumulation, cosine LR scheduling, and weight tying — the exact patterns production teams use.

Diagram of a mixed-precision training loop with gradient checkpointing for a mini GPT.

Build a Mini GPT From Scratch: A Mixed-Precision Training Loop That Actually Impresses

Ship a portfolio project that signals real systems skill: a custom autograd engine, mixed-precision training, gradient checkpointing, and AdamW, all wired into a mini GPT you can actually run.

Layered neural network diagram showing low-rank adapter matrices branching off frozen weights.

Building a LoRA Training Loop From Scratch in Pure NumPy

Build a working LoRA fine-tuning loop in pure NumPy, computing every gradient by hand through low-rank adapters. A practical side project that demonstrates real systems understanding to hiring managers.

Diagram of mixed-precision AdamW with ZeRO-1 sharding across GPUs.

Building Mixed-Precision AdamW with ZeRO-1 from Scratch in Pure PyTorch

A runnable, from-scratch implementation of mixed-precision AdamW with dynamic loss scaling and ZeRO-1 sharded optimizer state in pure PyTorch — built to demonstrate real systems engineering, not just model design.

Diagram of a mini GPT training pipeline showing token embeddings, attention, MLP blocks, and an optimizer loop.

Build a Mini GPT From Scratch in Pure NumPy: A Hiring-Manager-Worthy Project

Build a tiny GPT end-to-end in NumPy to demonstrate ownership of the ML stack: mixed precision, AdamW, cosine LR, and gradient accumulation. Code-first, with a roadmap to production-grade upgrades.