LangChain Embeddings Breakdown: Why Your AI Model Needs This | LangChain Tutorial

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Welcome to Part 6 of LangChain Tutorial — In this comprehensive LangChain tutorial, you will get to know about LLM Embeddings with Code — learn how AI understands meaning, context, and text similarity using vectors in this 2025 LangChain tutorial. 💻 Complete code walkthrough included to help you implement everything step-by-step. GitHub: https://github.com/Sumit-Kumar-Dash/Langchain-Tutorial/tree/main Langchain Full Course: https://www.youtube.com/watch?v=xLjyeeCNHrI&list=PLAgxe7DpTXmei0IV7-u9Zt9aoWP3eAHRg&index=1&t=3s&pp=gAQBiAQB 🔥LinkedIn: https://www.linkedin.com/in/sumit-kumar-dash-315378140/ 🔗 Related Playlists : Generative AI Full Course 2025: https://www.youtube.com/watch?v=3uMQnWCIkDg&list=PLAgxe7DpTXmdwTd1m6em5xeFCcUN6tvWm&index=1&t=505s&pp=gAQBiAQB Official Data Scientist Roadmap 2025: https://www.youtube.com/watch?v=BW49QAfLunQ&list=PLAgxe7DpTXmdAbTjrvIdt63LVQWP3j9Tx&index=1&pp=gAQBiAQB Timestamps: 00:00 – Welcome! Learn About Embeddings 00:35 – What Exactly is Text Embeddings? 06:30 – How to calculate Similarity Scores 🔍 11:15 – Full Code Demo Starts Here 26:30 – Final Takeaways & What’s Coming Next 🎯 #langchain #python #generativeai #datascience #skdneuron 👉 Don’t forget to like, share & subscribe 🔔 SKD Neuron that breakdown to help others avoid the same pitfalls!