440 items · Page 10 of 10
Create a free account to keep your reading organized, join thoughtful discussions, and get more from every chapter.
Free to join · Takes less than a minute
Why
I created this space so readers can learn together, ask questions, and make sense of difficult ideas.
Generalized linear models combine link functions with probability distributions. Covers logistic and Poisson regression, maximum likelihood, and Python.
Examines raw, log-scaled, boolean, augmented, and L2-normalized term frequency variants, with sparsity analysis and efficient computation using scikit-learn.
Explains how perplexity measures language model quality through cross-entropy and information theory.
Explains how n-gram language models assign probabilities to word sequences using the chain rule, Markov assumption, and MLE.
Covers smoothing techniques that solve the zero probability problem in n-gram models, from simple add-k smoothing through Good-Turing estimation to Kneser-Ney.
Covers regular expressions for text processing, covering metacharacters, quantifiers, lookarounds, and practical NLP patterns.
Covers OpenAI's ChatGPT release in 2022, including the conversational interface, RLHF training approach, safety measures.
Examines Mixtral 8x7B's sparse architecture and top-2 expert routing. Explains how MoE models match Llama 2 70B quality.
Create a free account to keep your reading organized, join thoughtful discussions, and get more from every chapter.
Free to join · Takes less than a minute
Why
I created this space so readers can learn together, ask questions, and make sense of difficult ideas.