Dashboard
12 weeks from linear algebra to a benchmarked, fused LLM + ML analysis system. Every lesson ships an artifact that feeds that week's build milestone.
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Sections
0 · Setup
0/4Environment, repo, DuckDB, and first data. Everything else stands on this.
1 · Linear Algebra & Statistics
0/7The math under both the ML methods and the benchmark you will defend.
2 · Classical ML on Tabular Data
0/9The executor's methods: sklearn, boosting, the two topic-cited papers, and DuckDB at a billion rows.
3 · Neural Nets to Transformers
0/5Build backprop, then a GPT, so the planner LLM is a machine you understand, not magic.
4 · LLM Application Engineering
0/9Structured outputs, tool use, planner, narrator, firewall: the Kestrel system itself.
5 · Benchmarking & Writeup
0/6Ground truth, baselines, ablations, and the Heilmeier report that makes it all defensible.
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