Книга Probabilistic Machine Learning — продолжение знаменитого Machine Learning: A Probabilistic Perspective.
Что внутри: ➡️ систематизация ключевых идей ML последних 30 лет, ➡️ от MCMC и вариационного вывода до современных генеративных моделей и диффузионных процессов, ➡️ параллели между графовыми моделями и Bayesian deep learning, ➡️ глубокий, но при этом доступный стиль изложения.
Книга Probabilistic Machine Learning — продолжение знаменитого Machine Learning: A Probabilistic Perspective.
Что внутри: ➡️ систематизация ключевых идей ML последних 30 лет, ➡️ от MCMC и вариационного вывода до современных генеративных моделей и диффузионных процессов, ➡️ параллели между графовыми моделями и Bayesian deep learning, ➡️ глубокий, но при этом доступный стиль изложения.
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