Eugene Yan • 8/16/2020

NLP for Supervised Learning - A Brief Survey

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This article provides a detailed chronological survey of major developments in Natural Language Processing (NLP) for supervised learning. It covers the evolution from sequential models (RNN, LSTM, GRU) and word embeddings (Word2Vec, GloVe) to contextual embeddings (ELMo), the attention mechanism (Transformer), and pre-trained models (GPT, BERT, T5). The author explains the core concepts, improvements, and historical context of each milestone.

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#Machine Learning #Neural Networks #Deep Learning
NLP for Supervised Learning - A Brief Survey

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