All “Basics of Machine Learning” classes look similar. We got a clear goal, perfect datasets, and a set of metrics to test our models. Then the working reality comes and it’s nothing like the artificial environment we were living in. The data is messy, the goal unclear and we need to come up with a solution that will make everybody happy (or at least not raging with pitchforks at our doors).

All “Basics of Machine Learning” classes look similar. We got a clear goal, perfect datasets, and a set of metrics to test our models. Then the working reality comes and it’s nothing like the artificial environment we were living in. The data is messy, the goal unclear and we need to come up with a solution that will make everybody happy (or at least not raging with pitchforks at our doors).

Artykuł What is under the hood of Discover section? pochodzi z serwisu Vived.