27K views · 1.9K reactions | The new Machine Learning Specialization...
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27K views · 1.9K reactions | The new Machine Learning Specialization...
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Building a machine learning model isn’t just about finding the right algorithm—it’s about the right process. In Machine Learning in Production, Andrew Ng breaks down the iterative loop of model development: training, error analysis, refining hyperparameters, and improving data. Getting to a high test set accuracy is one thing, but aligning your model with real-world business metrics? That’s where the real challenge begins. Learn how to bridge the gap between models and impact: https://hubs.la/Q0
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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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morning view sunrise ☀️ || adventures world , Life journey, special moments || important Consistency
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YouTubeRishabh Pandey
Deepak Jose | Data Science & Gen AI on Instagram: "Becoming an AI Engineer in 2026 isn’t about learning everything…� It’s about learning the right thing in the right order. Save this. This will guide your entire 2025. 💚⚡ 📊 Math & Statistics Resource: Khan Academy – Statistics & Probability 🐍 Python Resource: freeCodeCamp – Python Full Course 🤖 Classical ML Resource: Andrew Ng — Machine Learning (Coursera) 🚀 Advanced ML Resource: StatQuest — Advanced ML Pla
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2.2.1 Normal Equation by Andrew Ng
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