University · Data Science · Natural Language Processing for Data Science
Sentiment Analysis, Named Entity Recognition, and Text Classification
4 Abschnitte1 Karteikarten-Decks1 Quizze
A practical survey of core NLP application tasks — sentiment analysis, named entity recognition, and text classification — covering both classical and modern deep learning approaches.
Inhaltsübersicht
- Text Classification: Foundations and Methods
- Sentiment Analysis
- Named Entity Recognition (NER)
- Evaluation Metrics, Production Pipelines, and Applications
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- Text Preprocessing and Representation
- Classification, Sentiment Analysis, and Topic Modeling
- Large Language Models and NLP Applications
- Text Preprocessing: Tokenization, Stemming, Lemmatization, and TF-IDF
- Word Embeddings: Word2Vec, GloVe, and Contextual Representations
- Large Language Models: Transformers, BERT, and GPT Architecture
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