How not to make Machine's Learn

Machine Learning is fun. Atleast when the model is doing all fine and the accuracy is through the roof. But how do you debug when the model rolls with a lower score? How do you identify the bottleneck? The beginner instinct is usually: “Maybe I need a better algorithm.” Sometimes, yes. But wait give this a read: But a lot of ML failures are not algorithm failures. This article is a practical map of the common places where ML systems break. Also, i have kept this supershort coz no one needs story in the starting, This is for quick notes. Enjoy 1.