Build status
What is live on the site today, and what is still to be written. This page is generated from content/roadmap.yml — update that file and it updates here.
Platform
The site itself — how pages are built, verified, and shipped.
- Static site generatorDone
Markdown in content/ builds to HTML in _site/. Multi-course aware: adding a course needs a directory, a course.yml, and Markdown files — no code change.
- Design systemDone
Blueprint theme with per-track accent colours, DM Sans / Fira Code, and full dark mode driven by the viewer's system setting.
- Math, diagrams, and code renderingDone
KaTeX for inline and display math; Mermaid diagrams with pan, zoom, and full-size view; syntax-labelled code blocks; scrollable tables.
- Continuous deploymentDone
Pushes to main build and publish to GitHub Pages automatically. Pull requests run the same build without deploying.
- Build verificationDone
Every deploy is gated on a check suite asserting that each source file produced a page, every internal link resolves, every diagram rendered, and math survived the pipeline. A static site fails silently; this is what stops a broken link from shipping.
- Custom domain and HTTPSDone
mlinterviewnotes.com, served over TLS.
- Diagram correctness auditDone
All 67 course diagrams were checked twice — mechanically, that every one parses and renders; and semantically, that each agrees with the prose around it and with the reference implementation. 55 were correct as written, 12 carried inaccuracies, and all 12 are now fixed. No diagram was found to teach anything false.
- Interactive widget supportDone
Pages can embed raw HTML blocks and pull in their own scripts, so D3-driven explanations live alongside ordinary Markdown.
- Site-wide searchPlanned
Client-side index across all courses and notes. No backend needed at this scale.
- Contribution guidePlanned
A CONTRIBUTING.md covering the Markdown conventions, how to preview locally, and what the verification pass checks.
Courses
Long-form, sequential material built from first principles.
- Transformers Deep Dive — 17 modulesDone
From "why did we abandon RNNs?" through to the configuration choices in production 2026 models. Includes 67 diagrams, worked numeric examples, self-check questions, and a runnable reference decoder.
- Classical ML refresherPlanned
Linear and logistic regression, trees and ensembles, SVMs, clustering — derived rather than recited.
- LLM training and fine-tuningPlanned
Pretraining, SFT, preference optimisation, LoRA and friends.
Notes
Topic-by-topic reference notes. Structure is in place; the writing is not. Each topic below is a page waiting to be written.
- Math for ML — 1 of 5 writtenIn progress
Linear Algebra is written, with five interactive visualizations — recovered from the previous site, where it was the only topic that had real content. Calculus, probability and statistics, optimization, and discrete mathematics are still to come.
- Libraries for ML — 6 topicsIn progress
Structure listed; content pending.
- Machine Learning — 6 topicsIn progress
Structure listed; content pending.
- Deep Learning — 6 topicsIn progress
Structure listed; content pending.
- NLP — 6 topicsIn progress
Structure listed; content pending.
- One page per topicDone
Notes are two levels: a category page lists its topics, and each written topic is its own page beneath it — /notes/math/ holds /notes/math/linear-algebra/. A topic never sits beside the category it belongs to.
Sections still to build
Planned in the original site and carried forward here. Both were empty in the previous database, so both start from scratch.
- Question & AnswerPlanned
Interview questions with worked answers, explanations, and code — organised by category and difficulty.
- System DesignPlanned
ML system design patterns: problem statement, architecture, key components, scaling considerations, and trade-offs.