How to build a Q&A AI in Python (Open-domain Question-Answering)
🎁 Free NLP for Semantic Search Course:
https://www.pinecone.io/learn/nlp

How can we design these natural, human-like Q&A interfaces? The answer is open-domain question-answering (ODQA). ODQA allows us to use natural language to query a database.

That means that, given a dataset like a set of internal company documents, online documentation, or as is the case with Google, everything on the world’s internet, we can retrieve relevant information in a natural, more human way.

🌲 Pinecone article:
https://www.pinecone.io/learn/retriever-models/

🔗 Nils YT Talk: https://youtu.be/XNJThigyvos?t=118
🔗 MNR Loss Article: 
🔗 Free Pinecone API Key: https://app.pinecone.io/

🤖 70% Discount on the NLP With Transformers in Python course:
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00:00 Why QA
04:05 Open Domain QA
08:24 Do we need to fine-tune?
11:44 How Retriever Training Works
12:59 SQuAD Training Data
16:29 Retriever Fine-tuning
19:32 IR Evaluation
25:58 Vector Database Setup
33:42 Querying
37:41 Final Notes