Companies are obsessed with complex machine learning models.
They want to use deep learning for all their problems. The problem is that these tools require a lot of data scientists' time, which is expensive.
It turns out that simple statistical models are more than enough for most business problems! This blog post explains why they are beneficial for businesses. This alone can make or break a data science project.
Simple statistical models work well in practice because they are easy to implement and explainable (e.g., "a customer's probability of purchasing our product increases by X% when he gets older").
The #1 Mistake Companies Make When Creating Their Data Science Foundation
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