Библиотека дата-сайентиста | Data Science, Machine learning, анализ данных, машинное обучение

🔍 ML после релиза: почему модель может сломаться — и как это вовремя заметить

Внедрили модель, подтвердили гипотезу, получили эффект — работа сделана? Увы, нет.

После деплоя начинается настоящее испытание:
— данные меняются,
— поведение пользователей эволюционирует,
— а ваша модель может незаметно терять эффективность.

📌 Must-read для тех, кто работает с ML в продакшене и хочет, чтобы решения были устойчивыми, а не разовыми.

👉 Читайте, делитесь и не забывайте наблюдать за своими моделями: https://proglib.io/sh/fjpFLVWn8Z

Библиотека дата-сайентиста

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1.3K viewsMay 27 at 17:52

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Create: 2025-05-27
Last Update: 2025-06-01 09:45:47

BY Библиотека дата-сайентиста | Data Science, Machine learning, анализ данных, машинное обучение

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Look for Channels Online

Pinterest (PINS) Stock Sinks As Market Gains

🔍 ML после релиза: почему модель может сломаться — и как это вовремя заметитьВнедрили модель