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title = "Markov lesson: Applications and Further Reading"
priority = 7
status = "done"
ticket_type = "task"
dependencies = []
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Write Section 10 of edu/markov.md: 'Applications and Further Reading'\n\nLearning objectives:\n- Survey real-world applications: PageRank, MCMC, HMMs, RL, bioinformatics\n- Give a 2–3 sentence description of each application and how Markov chains appear\n- Point to concrete next steps for learners who want to go deeper\n\nContent to produce:\n- Application survey (5–7 topics, each 2–3 sentences)\n- Annotated reading list:\n * 'Introduction to Probability' (Blitzstein & Hwang) — free PDF\n * 'Markov Chains' (Norris) — rigorous treatment\n * Sutton & Barto 'Reinforcement Learning' — RL connection\n * The Metropolis-Hastings algorithm article on Wikipedia\n- Rust ecosystem pointers (crates for probabilistic modelling)\n\nTarget: replace the stub in edu/markov.md §10