Learn RAG from Scratch - GenAI RAG LLM Retrieval Strategies and Algorithms | Ranking Algorithms | Learn RAG from Scratch

Master RAG & Build 9 Real-World GenAI Projects from Scratch

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19 learners

What you'll learn

Explain the core concepts of RAG and why it mitigates LLM hallucinations.
Implement text chunking and create vector embeddings for a RAG pipeline.
Build a functional RAG system using LangChain, a vector database, and an LLM.
Deploy a RAG application with a user interface for document-based question answering.

This course includes

2.5 hours of video
Certificate of completion
Access on mobile and TV

Summary

Keywords

Krish Naik machine learning Krish Naik data science Retrieval-Augmented Generation RAG retrieval process VectorDB Vector-based retrieval similarity metrics Cosine Similarity Euclidean Distance ANN search TF-IDF BM25

Full Transcript

Welcome to the FreeBirds Crew and our RAG Playlist! 🎥 In this Part 4, we dive deep into the retrieval process in Retrieval-Augmented Generation (RAG) to discover how perfect context is found for queries. We’ll explore: 1. What is retrieval in RAG? 2. Techniques like vector-based retrieval, sparse retrieval, hybrid retrieval, and neural models. 3. Ranking algorithms for refining results. 4. NLP techniques to optimise context, such as tokenisation, indexing, and more. Watch as we break down algorithms like ANN Search, TF-IDF, BM25, DPR, and ColBERT—all with Python code examples! 🐍 Enhance your RAG system’s performance with practical tips and insights. 🔔 Subscribe to the FreeBirds Crew for more RAG and LLM tutorials from beginner to advanced levels. Let’s get started! 🚀 📂 RAG Playlist: https://bit.ly/3Zl47KD 💬 Have questions or ideas? Drop them in the comments! Join this channel to get access to perks: https://www.youtube.com/channel/UC4RZP6hNT5gMlWCm0NDzUWg/join 🚀 Follow me on Medium for the latest blogs and projects: https://bit.ly/3JGXqwc 🗂️ To get the Source Code, Follow me on GitHub: https://bit.ly/3gg07Uc 🔖 Book your call with me at topmate.io and learn how to harness the latest technologies power and speed up your learning process. 📲 Book your call at https://bit.ly/43TLDCD Playlists that make you skilled up 📍 Prompt Engineering: https://bit.ly/42v376M 📍 Finacial Data Analysis and Financial Modelling: https://bit.ly/3OCWI5O 📍 Artificial Intelligence Projects: https://bit.ly/3L8lhEi 📍 Predict IPL 2023 Winner: https://bit.ly/3BfC3N9 📍 Machine Learning: https://bit.ly/3gsuIxb 📍 Face Recognition: https://bit.ly/2YphpHm 📍 Creative Python: https://bit.ly/34nM9wr 📍 Latest Tech Videos: https://bit.ly/2QcaOeW 📱Follow US on social media. Telegram: https://bit.ly/3JJblSC Youtube: https://bit.ly/38gLfTo Instagram: http://bit.ly/2N1IMP9 - Twitter: https://bit.ly/40vYMjl ⚡️ Do like, comment, share, and subscribe to our YouTube channel for more videos and projects. Krish Naik genai, Krish Naik llm, Krish naik rag, krish naik vector databases, Krish Naik Python tutorial, Krish naik explainable ai, Krish Naik data science, Krish Naik statistics, machine learning full course, machine learning tutorial, machine learning interview questions, machine learning projects in Python, data science for beginners, data science project, data science full course, data science interview questions, data science interview, machine learning interview questions, statistics interview questions, Python interview questions, interview questions, leetcode questions, interview preparation for FAANG, FAANG Interview questions, Google data science Interview questions, Amazon data scientist interview, Meta data scientist interview questions,

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