RAG Pipeline Deep Dive
> Explain RAG pipeline End to End in detail?(questions involved in chunking strategies, Retrieval mechanisms)
> Is RAG fine-tuning method, Why is RAG not a fine-tuning method?
> What is the role of context window in RAG?
> How are embeddings and semantic search used for retrieval?
> How do you evaluate RAG in Production?
Deep Learning
> Explain differences and use cases of RNN and LSTM?
> What are the main issues with RNNs and how do Transformers overcome them?
> What is attention mechanism?
> What are actually Query, Key, Value in attention mechanism?
> Activation Function in Transformers?
Imagine you running a pizza franchise and struggling with no-shows after orders are placed. What features would you include in a model to predict which customers might not show up?
Day 46 of my #DSA challenge!
Solved 3 problems - Leetcode
1732. Find the Highest Altitude
1480. Running Sum of 1d Array
1588. Sum of All Odd Length Subarrays
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