Category: Data Science

My Ground Rules – Data Analysis “Before & After”

In my opinion there are many different ways & techniques to analyze the data and every individual brings in their own flavor to it which is unique & exciting to learn from. Through this article I wanted to focus more on the key ground rules (non-technical ones, as per me) to keep in mind before…
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February 9, 2020 0

What I learned from over 100 Data Science Interviews at Amazon

Interviewing is a very subjective process. Each role, candidate, and interviewer is different, and therefore there can’t be a strict set of “rules” that specify how it is best done. This article is purely a set of learnings gained from interviewing many candidates throughout my career to date, including over 100 Data Science & Analytics…
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February 6, 2020 0

The sense behind the data

In the world of data we are surfing, one of the most relevant things is to have a clear overview about what you are looking for to do the right questions. Having a huge amount of data could be nothing without sense, so giving sense to the data is more important than having data. The…
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January 13, 2020 0


Brief recap of the Open Data Science Conference – San Francisco, October 2019 On AI ROI: the questions you need to be asking Kerstin Frailey Metis Success is unpredictable in AI – feasibility is often unknown before a project has begun. Projects are esoteric – require highly specialized training. Application is new – methods to…
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December 29, 2019 0

2019 Year in Review – Kate Strachnyi

Link to video of 2019 Year in Review January Launched the Datacated Weekly challenge – close to 300 posts Started the Online Book Club – LinkedIn Group – over 1,500 members Story by Data became a Community Partner with ODSC February Vacation to Dominican Republic Joined the IADSS Advisory Board First ultra-marathon (50k trail run)…
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December 28, 2019 0