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7. Guide to the Final Stage: Response Generation in Simple RAG

Oct 10, 20246 min read20 views

Welcome to the seventh and final article in our series on Retrieval-Augmented Generation (RAG) explaining the stpes. In the previous articles, we...

7. Guide to the Final Stage: Response Generation in Simple RAG

Why Shift to CNNs: Solving Simple Neural Network Limitations and Understanding CNN [part1]

Oct 3, 20245 min read29 views

Today, we’re excited to explore one of the most widely used neural networks, especially in image processing: Convolutional Neural Networks (CNNs). You...

Why Shift to CNNs: Solving Simple Neural Network Limitations and Understanding CNN [part1]

Neural Networks Simplified: The Future Beyond Traditional ML

Sep 28, 20245 min read36 views

In recent years, we've been hearing a lot about deep learning and machine learning. Like many others, I was once confused, thinking deep learning was...

Neural Networks Simplified: The Future Beyond Traditional ML

6. Understanding Retrievers in detail -LangChain Retriever Methods

Sep 26, 20247 min read45 views

This is the 6th article in my Retrieval-Augmented Generation (RAG) series. In previous articles, we explored what RAG is and how to create a vector...

6. Understanding Retrievers in detail -LangChain Retriever Methods

5.Vector Stores: Efficient Storage and Retrieval for Embeddings

Sep 12, 20247 min read58 views

In this continuation of our series of Retrieval-Augmented Generation (RAG), we will learn about the final step of the ingestion pipeline—vector...

5.Vector Stores: Efficient Storage and Retrieval for Embeddings

4. Embeddings Explained - Next in RAG Series

Sep 7, 20243 min read50 views

In our previous article, we explored and discussed the concept of splitting documents into chunks. Now, we'll talk next crucial step: embeddings. For...

4. Embeddings Explained - Next in RAG Series