The challenge of putting ML into practice

This talk originates from the archive. To the CURRENT program
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Wednesday, December 5 2018
15:00 - 15:30
Salon 10

It has not been long since the moment when ML transferred from a purely academic discipline, to a technology that is actively being implemented in business. Because of that, it is a common
situation when specialists encounter problems they did not have while doing research or participating in competitions (e.g. Kaggle). At the same time, companies that want to introduce ML in their business process, often do not realize what is needed for that to happen, what difficulties might occur and how to estimate the outcome of a project. We will look at two projects implemented in production: carotid artery examination and vehicle behavior analysis.  Based on those examples we will cover some of the problems you might encounter in your projects including the fields of data processing, algorithm selection, communication with the customer and other.

We will go through the most significant challenges faced during the development, how they were dealt with and what are the general options. In your future projects, you will probably encounter these and other problems, but this talk will make you a little more prepared for them, whether you are a developer or an entrepreneur.

Behind the Tracks