— In the News —
Yoshua Bengio, Geoffrey Hinton and Yann LeCun have been named as recipients of what is often referred to as the “Nobel Prize of Computing." This announcement from the ACM highlights the key research and papers that drove their careers.
Tricky issues here. Companies are offering services in exchange for health data that doesn't get shared back. Who owns that data? And if it can be sold, what happens if third parties, such as insurance companies or employers, get access to it? Some users are revolting. And there's a cost for that.
— How-to —
Or, how to teach stats: It's so simple we should only teach regression.
Awesome article by Kevin Marham at Data School that reviews six ways to share fully interactive notebooks in the cloud. This is very well organized and presented. Includes recommendations for specific use-cases and lots of useful links.
There's no code here but it's a fantastic walk-through of how to build a system that games social media. This is a fun read that's written from the perspective of a data-savvy engineer.
— Videos, Talks & Courses —
Chapter 1 of Grant Sanderson's latest project is a great visual introduction to differential equations. Grant is a master at crafting animated explanations that are easy to follow.
Stanford's CS224N is a popular and well-known course for learning about natural language processing. The lectures and course materials for the latest iteration of the course were recently made available online and the sylabus includes links to a well-curated collection of readings.
— Data Viz —
In this visual walk-through of The Economist's "crimes against data visualization," Sarah Leo explores a collection of bad charts and shows how they can be easily fixed by employing some practical rules of thumb.
— Career —
This in-depth Guide from Dataquest covers a wide variety of topics about data science careers, including job titles, finding jobs, project portfolios, applications, interviews, and negotiation strategies. This is a must-read if you think you might be on the job market in the next couple of years.
Interested in becoming a data science leader? Here are some real-world insights into what that path can look like and what it takes to succeed.