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Welcome to Learn RAG from Scratch Series, This is our first project in this series and In this step-by-step tutorial, you'll learn how to create a cutting-edge Retrieval-Augmented Generation (RAG) application. Using LangChain, ChromaDB, and HuggingFace Transformers, we’ll build a system that retrieves relevant document chunks and generates context-aware answers using Large Language Models (LLMs). Learn RAG from Scratch Last 4 Videos: https://bit.ly/3Zl47KD What You'll Learn: 1. How to preprocess and vectorize documents with LangChain 2. How to use ChromaDB for efficient similarity searches 3. How to integrate embeddings and retrieval into the workflow 4. How to generate accurate, context-aware answers using LLMs 5. How to build an interactive UI with Streamlit Whether you're a beginner or a seasoned developer, this project showcases the power of RAG systems and their applications in AI-driven solutions. Technologies Used: 1. LangChain 2. ChromaDB 3. Hugging-Face Transformers 4. Streamlit Source Code: https://github.com/simranjeet97/GenAI_LLM_RAG_Tutoring_System Follow me on LinkedIn: https://www.linkedin.com/in/simranjeet97/ Have Questions? Drop them in the comments! Join this channel to get access to perks: https://www.youtube.com/channel/UC4RZP6hNT5gMlWCm0NDzUWg/join Don’t forget to: Like this video, subscribe to the channel and Comment your thoughts or questions 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 Follow me on Medium for the latest blogs and projects: https://bit.ly/3JGXqwc Playlists that make you skilled up 1. GenAI Full Course with LLM Fine Tuning and Evaluation: https://bit.ly/4bJwZla 2. Learn RAG from scratch with GenAI projects: https://bit.ly/3Zl47KD 3. Latest AI/GenAI Research Papers Explained: https://bit.ly/4huqEMT 4. RAG and LLM Use Cases in Finance Domain Projects: https://bit.ly/3AGSRQm 4. Prompt Engineering: https://bit.ly/42v376M 5. Financial Data Analysis and Financial Modelling: https://bit.ly/3OCWI5O 6. Artificial Intelligence Projects: https://bit.ly/3L8lhEi 7. Predict IPL 2023 Winner (End to End Data Science Project): https://bit.ly/3BfC3N9 8. Explainable AI (XAI) Machine Learning: https://bit.ly/3gsuIxb 9. Face Recognition: https://bit.ly/2YphpHm Youtube Tags: 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, learn rag from scratch, rag tutorials, rag llm tutorials, rag llm project, genai projects, genai techning assistant, genai final year project, genai project,
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