Time Series Analysis: When “Good Enough” is Good Enough

My today’s talk at PyCon Israel in a post format.

Data for Breakfast

Being highly professional, many data scientists strive toward the best results possible from a practical perspective. However, let’s face it, in many cases, nobody cares about the neat and elegant models you’ve built. In these cases, fast deployment is pivotal for the adoption of your work — especially if you’re the only one who’s aware of the problem you’re trying to solve.

This is exactly the situation in which I recently found myself. I had the opportunity to touch an unutilized source of complex data, but I knew that I only had a limited time to demonstrate the utility of this data source. While working, I realized it’s not enough that people KNOW about the solution, I had to make sure that people would NEED it. That is why I sacrificed modeling accuracy to create the simplest solution possible. I also had to create a RESTful API server, a visualization…

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