How to Build a Q&A AI in Python - Open-Domain Question-Answering

Learn how to build an open-domain question-answering (ODQA) AI system in Python. Explore the fundamentals of natural language processing for semantic search, including retriever models, fine-tuning techniques, and evaluation methods. Discover how to set up a vector database, implement querying functionality, and create human-like Q&A interfaces. Gain insights into the importance of ODQA systems, training data preparation, and the use of tools like Pinecone for efficient information retrieval.

Why QA
Open Domain QA
Do we need to fine-tune?
How Retriever Training Works
SQuAD Training Data
Retriever Fine-tuning
IR Evaluation
Vector Database Setup
Querying
Final Notes