Natural Language Processing

Learning Objective

Acquire skills in applying NLP techniques for text-based data analysis and generation.

Related Skills

1. Preprocessing and vectorizing text data
2. Implementing advanced language models for various NLP tasks
3. Deploying NLP models in production environments

###Subtopics 1. Text data preprocessing (tokenization, stopword removal, stemming/lemmatization) 2. Text vectorization techniques (one-hot, TF-IDF, word embeddings) 3. Recurrent neural networks for text generation (LSTMs, Transformers) 4. Transfer learning with pre-trained language models (BERT, GPT) 5. Named entity recognition, sentiment analysis, and text classification

References and Resources

- "Natural Language Processing with Python" by Steven Bird et al.
- "Hands-On Natural Language Processing with Python" by Rajesh Arumugam and Nipun Batra
- Coursera course "Natural Language Processing Specialization" by deeplearning.ai