Tweeted By @Al_Grigor

8 reasons machine learning projects fail - by @elenasamuylova

🔸 Doing ML for wrong reasons
🔸 ML not needed
🔸 Bad data
🔸 Poor problem framing
🔸 Model ≠ product
🔸 Bad infrastructure
🔸 No trust from stakeholders
🔸 Production failures

Solution? 👉 https://t.co/mvs7sJyxDe pic.twitter.com/poTAzwWT4b

— Alexey Grigorev (@Al_Grigor) February 21, 2021