Stanford CS229: Machine Learning Course, Lecture 1 - Andrew Ng (Autumn 2018)
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Stanford's Visionary: Dr. Andrew Ng Unlocks the Next Frontier in AI
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More than 100 years ago, electricity changed everything. Now the same thing is about to happen with artificial intelligence. Watch Andrew Ng’s full talk from the Stanford MSx Future Forum: http://stanford.io/2pzQM2z | Stanford Graduate School of Business
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Lec 1 - Machine Learning (Stanford)
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New Course: Reinforcement Fine-Tuning LLMs with GRPO! Learn to use reinforcement learning to improve your LLM performance in this short course, built in collaboration with Predibase, and taught by Travis Addair, its Co-Founder and CTO, and Arnav Garg, its Senior Engineer and Machine Learning Lead. Reasoning models have been one of the most important developments in LLMs. Reinforcement Fine-Tuning (RFT) uses rewards to encourage LLMs to find solutions to multi-step reasoning tasks such as solving
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New short course: Evaluating AI Agents! Evals are important for driving AI system improvements, and in this course you'll learn to systematically assess and improve an AI agent’s performance. This is built in partnership with Arize AI and taught by John Gilhuly, Head of Developer Relations, and Aman Khan, Director of Product. I've often found evals to be a critical tool in the agent development process - they can be the difference between picking the right thing to work on vs. wasting weeks of e
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