Sentiment Analysis

Summary

Classifying text by expressed sentiment (positive/negative/neutral) — one of the most common practical NLP tasks and a good first classification project.

How to Learn This

1Build a sentiment classifier with TF-IDF + logistic regression as a baseline.
2Then fine-tune a pretrained transformer model and compare accuracy.
3Test your model on ambiguous or sarcastic text to see where it breaks.

Named Entity Recognition

Hugging Face Transformers Library

More topics in Natural Language Processing

Text Preprocessing (Tokenization, Stemming, Lemmatization)Bag of Words & TF-IDF Word Embeddings (Word2Vec, GloVe)Named Entity Recognition Hugging Face Transformers Library Pretrained NLP Models (BERT, RoBERTa)Sequence Classification Text Summarization Question Answering Models

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