Prompt Engineering Tutorial – Master ChatGPT and LLM Responses

This is the second of a series of 3 videos where we demystify Transformer models and explain them with visuals and friendly examples. 00:00 Introduction01:18 Recap: Embeddings and Context04:46 Similarity11:09 Attention20:46 The Keys and Queries Matrices25:02 The Values Matrix28:41 Self and Multi-head attention33:54: Conclusion

This is CS50, Harvard University’s introduction to the intellectual enterprises of computer science and the art of programming. TABLE OF CONTENTS 00:00:00 – Welcome00:01:01 – Introduction00:03:13 – Image Generation00:08:23 – ChatGPT00:11:06 – Prompt Engineering00:12:40 – CS50.ai00:19:03 – Generative AI00:22:08 – Decision Trees00:26:33 – Minimax00:34:27 – Machine Learning00:42:56 – Deep Learning00:48:53 – Large Language Models00:53:36 –…

Timestamps:0:00 – Who this was made for0:41 – What are large language models?7:48 – Where to learn more

Get ready for a showdown between LangChain and LangGraph, two powerful frameworks for building applications with large language models (LLMs.) Master Inventor Martin Keen compares the two, taking a look at their unique features, use cases, and how they can help you create innovative, context-aware solutions.

In this video we will talk about backpropagation – an algorithm powering the entire field of machine learning and try to derive it from first principles. OUTLINE:00:00 Introduction01:28 Historical background02:50 Curve Fitting problem06:26 Random vs guided adjustments09:43 Derivatives14:34 Gradient Descent16:23 Higher dimensions21:36 Chain Rule Intuition27:01 Computational Graph and Autodiff36:24 Summary38:16 Shortform39:20 Outro Jürgen Schmidhuber’s blog…