When I was working as a data scientist at Apple in Silicon Valley, I’d drive up to San Francisco on nights and weekends to meet a girl for dinner or go to a meetup.
I sort of fell in love with the city, and …
You’ve probably read numerous articles telling you how to start learning data science. Collectively, they tell you to dozens of things you need to learn. Learn Python. Learn R. Learn Hadoop. They tell you all the skills you need: learn machine learning, visualization, data wrangling. Little technical skills like manipulating vectors, matrices, loops. More tools […]
I love cars. The way they sound. The engineering. The craftsmanship. And let’s be honest: fast cars are just fun. Given my love of cars, I frequently watch Top Gear clips on YouTube. A couple of weeks ago, I stumbled across this: Watching the video, I’m thinking, “253 miles per hour? You’ve got to […]
An important principle in analyzing data is “overview first, zoom and filter, then details on demand” (quote: Ben Shneiderman) In practice, this typically means starting at a high level with a single chart, and then “zooming into” the data by replicating that chart for specific subsets of the dataset. And, even more valuable is being […]
Last week, I was talking to a guy who’s learning analytics, coaching him on what skills to learn next and helping him plan a career path. He’s a smart guy with an analytical background and minor coding experience, but he’s new to R.
Towards the end of the conversation, I asked him, “what’s the biggest challenge you have right now, learning analytics.”
His response? “The code is intimidating.”