Hacker News Reader

I remember that class. Someone from Blackrock taught it at Hacker Dojo. The good old days of support vector machines and Matlab.

This was very important with classical machine learning, now with deep learning, feature engineering became useless as the model can learn the relevant features by itself.

However, having a quality and diverse dataset is more important now than ever.

That depends on the type of data, and regardless, your goal is to minimizing the input data since it has a direct impact on performance overhead and duration of inference.

no we just replaced feature engineering with architectural engineering

>was the importance of getting the features right.

Yeah, but also knowing which features to get right. Right?