It's true. Fun and relevant fact: The job title data scientist was invented at LinkedIn when they saw data analysts that needed to know R or Python skills. T

It's true. Fun and relevant fact: The job title data scientist was invented at LinkedIn when they saw data analysts that needed to know R or Python skills. These skills seemed different enough from the traditional Excel and SAS data analyst jobs at the time to warrant a new job title. So did Excel not cut it, or was it a preference to use Python? Back then Excel supported up to 65,535 rows, and would typically crash with over 8,000 rows. I worked in that era in Excel. One model once was split across three spreadsheets. Only one spreadsheet could be open at a time, they would take 20 minutes each to load, and there was about a 50% chance they would crash while loading. So what do you do if you need over 65,000 instances of labeled data? For a neural network it's nice to have a million instances, yes a million. R and Python have in them what is called a dataframe. It's a spreadsheet, but in another programming language. We tend to load our data into those, which is just like Excel, but without the hardware limitations. So in many ways, today it's just like it once was, but we get to choose which programming language to use while working in a spreadsheet, and let's be fair, the Excel programming language isn't exactly great.