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Lecture 2: Large Language Models (LLM) Basics
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Building LLMs from scratch - Lecture 2: Large Language Models (LLM) Basics

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This course includes

  • 30.5 hours of video
  • Certificate of completion
  • Access on mobile and TV

Summary

Full Transcript

In this lecture, we understand the basics of LLMs: (1) Introduction (2) Significance of the word “Large” in Large Language Models (3) LLMs vs Earlier NLP Models (4) LLM Secret Sauce: Transformers (5) Difference between the terminologies: LLM vs GenAI vs DL vs ML vs AI (6) Applications of LLMs The key reference book which this video series very closely follows is Build a Large Language Model from Scratch by Manning Publications. All schematics and their descriptions are borrowed from this incredible book! This book serves as a comprehensive guide to understanding and building large language models, covering key concepts, techniques, and implementations. Affiliate links for purchasing the book will be added soon. Stay tuned for updates! 0:00 Objectives of the lecture 2:05 What are Large Language Models (LLMs) 6:45 Why “Large” Language Models? 11:46 LLMs vs Earlier NLP Models 14:22 LLM Secret Sauce 17:56 LLM vs GenAI vs DL vs ML vs AI 25:47 Applications of LLMs ================================================= ✉️ Join our FREE Newsletter: https://vizuara.ai/our-newsletter/ ================================================= Vizuara philosophy: As we learn AI/ML/DL the material, we will share thoughts on what is actually useful in industry and what has become irrelevant. We will also share a lot of information on which subject contains open areas of research. Interested students can also start their research journey there. Students who are confused or stuck in their ML journey, maybe courses and offline videos are not inspiring enough. What might inspire you is if you see someone else learning and implementing machine learning from scratch. No cost. No hidden charges. Pure old school teaching and learning. ================================================= 🌟 Meet Our Team: 🌟 🎓 Dr. Raj Dandekar (MIT PhD, IIT Madras department topper) 🔗 LinkedIn: https://www.linkedin.com/in/raj-abhijit-dandekar-67a33118a/ 🎓 Dr. Rajat Dandekar (Purdue PhD, IIT Madras department gold medalist) 🔗 LinkedIn: https://www.linkedin.com/in/rajat-dandekar-901324b1/ 🎓 Dr. Sreedath Panat (MIT PhD, IIT Madras department gold medalist) 🔗 LinkedIn: https://www.linkedin.com/in/sreedath-panat-8a03b69a/ 🎓 Sahil Pocker (Machine Learning Engineer at Vizuara) 🔗 LinkedIn: https://www.linkedin.com/in/sahil-p-a7a30a8b/ 🎓 Abhijeet Singh (Software Developer at Vizuara, GSOC 24, SOB 23) 🔗 LinkedIn: https://www.linkedin.com/in/abhijeet-singh-9a1881192/ 🎓 Sourav Jana (Software Developer at Vizuara) 🔗 LinkedIn: https://www.linkedin.com/in/souravjana131/

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