This course provides a comprehensive introduction to Natural Language Processing (NLP) using advanced Deep Learning techniques. Students will engage with practical exercises in Python and Keras, exploring key concepts like Word and Text Embeddings, Recurrent Neural Networks (RNNs), LSTM, GRU, and Transformer models such as BERT.

Resources

Syllabus

Slides:

1. Introduction to Deep Learning for NLP
2. Language Models
3. Advanced NLP Models
4. Transformers Models

Notebooks

• Lecture 01
• Lecture 02
• Lecture 03
• Lecture 04