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Getting started with an ML project? Andrew Ng shares practical tips to set up a strong foundation—choosing a reasonable algorithm, running quick sanity checks, and focusing on data quality over chasing the latest models. These steps can save time, prevent errors, and make iteration more efficient. Streamline your workflow... show more

DeepLearning.AI

333,053 subscribers

11,307 просмотров • 1 год назад •via X (Twitter)

Образование Наука и технологии

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Private livecam show

Комментарии: 3

Фото профиля Jonas ️

Jonas ️1 год назад

Andrew Ng’s tips are spot on! Prioritizing data quality over chasing the latest models is key to efficient ML workflows. His courses are a must for any AI enthusiast! #aspie

Фото профиля opensourceCM

opensourceCM1 год назад

What’s the cost of mistakes in your contracts? If you work with contracts day-to-day, it’s time to automate. Track every detail, streamline workflows ... ✨ Make managing contracts as easy as a few clicks. Visit our new website & book your demo today!

Фото профиля DataInsta

DataInsta1 год назад

solid advice! a strong foundation makes all the difference in ml projects!

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