Pragmatically exploring and choosing tools for better Analytics
Scalling data science development
[Portuguese only] An interview with André Boechat conducted by Eduardo Bellani.
Personal experience on learning software development as a ‘data scientist’.
In many situations, unprepared data scientists can spend much more time than necessary on secondary tasks. Although their attention should stay on analyzing data, checking hypothesis, engineering features, etc., they often need to get their hands dirty and code auxiliary scripts and parsers to get the information they need.
Details on the thought process of adopting Go