30 Data Science Punchlines

30 Data Science PunchlinesA holiday reading list condensed into 30 quotesCassie KozyrkovBlockedUnblockFollowFollowingDec 20For those who like brainfood on your vacation, here’s a handy index of all my articles from 2018 boiled down to 30 (occasionally cheeky) punchlines to help you avoid/cause awkward silences at family events and holiday parties.Sections: Data Science and Analytics, ML/AI Concepts, How Not To Fail At ML/AI, Data Science Leadership, Technology, Statistics.Bonus: Videos, podcasts, foreign language translations for your non-English-speaking friends and family to enjoy, and an end-to-end deep learning tutorial for the Pythonistas among you.Data Science and AnalyticsWhat on earth is data science?.A quick tour of data science, data engineering, statistics, analytics, ML, and AI.Data science is the discipline of making data useful.Twitter definitions circa 2014.What Great Data Analysts Do — and Why Every Organization Needs Them..Good analysts are a prerequisite for effectiveness in your data endeavors..It’s dangerous to have them quit on you, but that’s exactly what they’ll do if you under-appreciate them.Each of the three data science disciplines has its own excellence..Statisticians bring rigor, ML engineers bring performance, and analysts bring speed.Secret Paragraphs from HBR’s Analytics A collection of musings omitted from the article above..Let’s talk about hybrid roles, the nature of research, Bat Signals, data charlatans, and awesome analysts!Buyer beware: there are many data charlatans out there posing as data scientists..There’s no magic that makes certainty out of uncertainty.Top 10 roles in AI and data science..A guide to the job titles, in hiring order.If a researcher is your first hire, you probably won’t have the right environment to make good use of them.ML/AI ConceptsThe simplest explanation of machine learning you’ll ever read..Machine learning is a thing-labeler where you explain your task with examples instead of instructions.Machine learning is exciting because it allows you to automate the ineffable.Are you using the term ‘AI’ incorrectly?.With poorly defined terms, there’s not really such a thing as using them correctly..We can all be winners, but here’s a quick guide to the alphabet soup of AI, ML, DL, RL, and HLI.If you’re worried that there’s a human-like intelligence lurking in every cupboard, breathe easy..All those industry AI applications are too busy solving real business problems.Explaining supervised learning to a kid (or your boss).. More details

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