You cannot select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
821 B
821 B
| title | status | type | priority | created_at | updated_at | parent |
|---|---|---|---|---|---|---|
| Markov lesson: Text Generation with Markov Chains | completed | task | high | 2026-03-10T23:30:01Z | 2026-03-13T22:37:26Z | edu-svom |
Write Section 6 of edu/markov.md: 'Text Generation with Markov Chains'\n\nLearning objectives:\n- Explain how words (or characters) become states in a text Markov chain\n- Define bigrams and how they form a transition table from a corpus\n- Discuss why generated text sounds locally plausible but globally incoherent\n- Introduce the concept of order-n chains and the tradeoff between coherence and novelty\n\nContent to produce:\n- 3–5 paragraphs of prose\n- A short worked bigram example from a 2-sentence sample text (show the table)\n- No code in this section\n\nTarget: replace the stub in edu/markov.md §6