Technology
Why you can't only rely on existing methods to evaluate your work, what to do when you don't have evaluation data, what to do when there is no ground truth, why some mistakes are much more important than others, and the importance of ongoing evaluations.
BTW, if you are not a data scientist yet, but want to become one, you should really attend our webinar. We will demystify the transition into data science. We will show you the most effective way to build your skills. And we will advise you on the four possible options you can take to go from where you are to landing a data science job in as little as 9 months. Find out more here.
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