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

www.tg-me.com/us/Библиотека data scientist’а | Data Science Machine learning анализ данных машинное обучение/com.dsproglib/6489

1.6K viewsMay 27 at 17:52

tg-me.com/dsproglib/6491

Create: 2025-05-27
Last Update: 2025-06-14 03:34:48

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

Share with your friend now:
tg-me.com/dsproglib/6491

Библиотека data scientist’а | Data Science Machine learning анализ данных машинное обучение Telegram | DID YOU KNOW?

Look for Channels Online

You guessed it – the internet is your friend. A good place to start looking for Telegram channels is Reddit. This is one of the biggest sites on the internet, with millions of communities, including those from Telegram.Then, you can search one of the many dedicated websites for Telegram channel searching. One of them is telegram-group.com. This website has many categories and a really simple user interface. Another great site is telegram channels.me. It has even more channels than the previous one, and an even better user experience.These are just some of the many available websites. You can look them up online if you’re not satisfied with these two. All of these sites list only public channels. If you want to join a private channel, you’ll have to ask one of its members to invite you.

That growth environment will include rising inflation and interest rates. Those upward shifts naturally accompany healthy growth periods as the demand for resources, products and services rise. Importantly, the Federal Reserve has laid out the rationale for not interfering with that natural growth transition.It's not exactly a fad, but there is a widespread willingness to pay up for a growth story. Classic fundamental analysis takes a back seat. Even negative earnings are ignored. In fact, positive earnings seem to be a limiting measure, producing the question, "Is that all you've got?" The preference is a vision of untold riches when the exciting story plays out as expected.

Библиотека data scientist’а | Data Science Machine learning анализ данных машинное обучение Telegram | DID YOU KNOW?

Look for Channels Online

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