Скачать или смотреть acquisition functions in bayesian optimization

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If you're new to ML, here are the 3 best books I recommend (I've personally read all of these):
1. Hands-On Machine Learning – the go-to practical ML guide: https://amzn.to/3UcGqSS
2. Mathematics for Machine Learning – deep dive into the theoretical aspects of ML: https://amzn.to/3IZgHe7
3. Designing Machine Learning Systems - practical strategies for building scalable ML solutions: https://amzn.to/4ojEqFX

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Summary
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Learn how acquisition functions like Probability of Improvement (PI), Expected Improvement (EI), and Upper Confidence Bound (UCB) work in Bayesian Optimization. This video explains how these functions guide intelligent sampling strategies, balancing exploration and exploitation, and why they outperform brute-force methods like grid search. Perfect for anyone in machine learning, AI, and optimization.

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