Learn NLP in Python — text preprocessing, machine learning, transformers & LLMs using scikit-learn, spaCy & Hugging Face
What you'll learn
- Review the history and evolution of NLP techniques and applications, from traditional machine learning models to modern LLM approaches
- Walk through the NLP text preprocessing pipeline, including cleaning, normalization, linguistic analysis, and vectorization
- Use traditional machine learning techniques to perform sentiment analysis, text classification, and topic modeling
- Understand the theory behind neural networks and deep learning, the building blocks of modern NLP techniques
- Break down the main parts of the Transformers architecture, including embeddings, attention and feedforward neural networks (FFNs)
- Use pretrained LLMs with Hugging Face to perform sentiment analysis, NER, zero-shot classification, document similarity, and text summarization & generation