Elle NLP for HealthPaper to Practice Language, data, and the foundations of NLP.
NLP Learning Notes ·
From hallucination and stale information through FActScore, DoveScore and RAG to RLHF, bias mitigation and interpretability: where the problems of large language models come from and how they can be reduced.
NLP Learning Notes ·
From three improvements on neural language models (tokens, longer context and attention) through the Transformer and the GPT and Llama families: prompting, in-context learning, chain-of-thought and models trained to reason.
NLP Learning Notes ·
From what every language model computes through embeddings, neurons, activation functions and backpropagation: how a neural network learns to predict the next word.
NLP Learning Notes ·
From letter and word frequencies through conditional probability and bigrams: how a simple language model scores a sentence and writes one word at a time.
NLP Learning Notes ·
From lexemes and word relations through WordNet and FrameNet: how computers build up to knowledge graphs, and what UMLS and MeSH do in medicine.
NLP Learning Notes ·
From tokens and sentence boundaries to POS tagging and named entity recognition: how text is split and labeled.
NLP Learning Notes ·
Connect word structure, normalization and regular expressions to understand how text becomes material for analysis.
NLP Learning Notes ·
Words, context, and vocal cues: an introduction to natural language processing and its connection to interview research.
