BigDataFr recommends: Why you should stop worrying about deep learning and deepen your understanding of causality instead
[…] Everywhere you go these days, you hear about deep learning’s impressive advancements. New deep learning libraries, tools, and products get announced on a regular basis, making the average data scientist feel like they’re missing out if they don’t hop on the deep learning bandwagon.
However, as Kamil Bartocha put it in his post The Inconvenient Truth About Data Science, 95% of tasks do not require deep learning. This is obviously a made up number, but it’s probably an accurate representation of the everyday reality of many data scientists.
This post discusses an often-overlooked area of study that is of much higher relevance to most data scientists than deep learning: causality. […]