— In the News —
When is it okay to grab data from someone else’s website, without their explicit permission? A new ruling by a federal judge in California might have dramatic implications on this question, and on the open nature of the web in general.
China is betting heavily on AI and with vast amounts of government data, a huge pool of engineers to do the work and investors plowing money into the field, it seems like a pretty good bet.
Remember Watson? The hype was fantastic. Here's what happened.
— Tools and Techniques —
Great exploration of Support Vector Machines with an emphasis on intuitive understanding over math. Covers use cases, how they work, how to judge the effectiveness of an SVM, kernels, libraries, and useful resources.
This project by Jake VanderPlas is a fast-paced introduction to Python, particularly for people that are doing data science and/or scientific programming.
Pandas is a popular and super useful analytics library. Here are some tricks to help you get the most of it.
SQL Zoo may have everything you'll ever need to know about SQL. Includes step-by-step SQL tutorials, an extensive reference, complex examples, and links to worthwhile resources.
— Data Viz —
There are lots of ways to put data on a map. This post explores key considerations and strategies for telling the best story with your map data.
— Career —
This is an awesome series by a recruiter who talks with data scientists everyday. It's a deep dive into the skills you need, best ways to learn them, and how to maximize your chances of getting the job you want.
In the past few weeks, Fast.ai released Part 2 of their Deep Learning for Coders course and Andrew Ng announced his Deep Learning Specialization series on Coursera. Both are already highly regarded but which should you choose? In this post, Andrew N describes his experience with both programs. Yes, he's completed both already and he has some suggestions.
— In Case You Missed It —
Be sure to catch the most popular links from last week's issue...