Natural Language Processing: A Comprehensive Tutorial
This article explores various aspects of natural language processing (NLP). The evolution of machine learning techniques, the significance of transformer architectures, and the role of attention mechanisms are highlighted. The article emphasizes the importance of data labeling, tokenization, and Vectorization. Then after a non-mathematical of Transformers, it goes into emergence of pre-trained models and the role of Hugging Face as a platform for accessing and utilizing these models effectively.
TABLE OF CONTENTS:
- Branches of NLP
- Machine Learning Pipeline in NLP
- Data Labelling
- Tokenisation
- Vectorization: Bag of Words, TF-IDF & Embedding Matrix
- Transformers
- Positional Encoding
- Attention Mechanism
- Encoder
- LLM
- BERT
