Deep Learning Techniques for Natural Language Processing
summary
Overview of methods and a working demo using Google Collab, NLTK and scikit‑learn on a Kaggle dataset of 130,000 reviews: builds a bag‑of‑words with CountVectorizer (1–2 grams, 5k→3k features), trains logistic regression on an 80/20 split, and reports ~59% accuracy. Covers RNNs (LSTM/GRU) and modern transformers as context, shows lemmatization/stemming, chunking, word clouds, and three live predictions (Pinot, Chardonnay, Zinfandel) that the model classifies correctly.
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chapters (8)
- 0:00Introduction to NLP
- 4:30History of NLP
- 8:00Modern NLP techniques
- 10:27Bag of words demo
- 17:45NLTK toolkit overview
- 18:06Wine review classification
- 28:38Challenges and future of NLP
- 30:22Q&A and resources
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