Training & Fine-Tuning explainers.
Skip the 40-page docs. Every explainer turns a tricky AI, Claude Code, MCP, or cloud idea into a live, animated diagram you can drag, scrub, and break — so the concept finally clicks in minutes, not hours.
Every Training & Fine-Tuning explainer
Gradient Descent: Rolling Downhill to a Smarter Model
Training is a marble rolling down a wrinkled hill — the loss landscape. Tune learning rate and momentum to see it slide, oscillate, or get stuck.
Fine-Tuning vs RAG: When to Teach, When to Look Up
Fine-tuning changes what the model knows; RAG gives it a reference shelf at query time. Most "make the LLM know our docs" jobs are RAG jobs.
LoRA: Cheap Fine-Tuning Without Touching the Whole Model
LoRA freezes the giant model and trains tiny rank-r adapters next to it. 7B-param model, ~1% of the trainable weights, 99% of the quality.
Knowledge Distillation: Teaching a Small Model to Imitate a Big One
Distillation trains a small student model to mimic a big teacher's soft outputs. You ship the small one — much cheaper, surprisingly close in quality.
Stop reading about it. Start scrubbing it.
Stuck on an AI, Claude Code, or cloud concept? Tell me what's not clicking — I'll ship a free interactive explainer with the analogy, the animation, and the sliders, usually inside a week.
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