— In the News —
According to new data from Indeed, data-science job openings across the U.S. are expanding fast and driving salaries up too.
Google has a massive impact on the tools, applications and research that help steer the data science community. This 2018 retrospective by Jeff Dean is amazing in its scope.
— Insight —
When starting an analytics program, some teams do extensive planning upfront and then carefully execute that plan. Although that approach may feel safe, there's another path that's almost always more effective. This post by Benn Stancil tells a Tale of Two Teams...
— Sponsored Link —
Data science and analytics positions are taking the job market by storm. A master’s degree or graduate-level certificate from UW-Madison can jump start your data career. We have 13 online, one-year, full-time, or part-time data programs to fit your life and help you succeed, including GIS, Data Analytics and Actuarial Science. Explore more today.
— Tools and Techniques —
This is a nice overview of the recent rstudio::conf, organized around 3 key themes: Serious Shiny, R in Production, and Data Science Skill Growth. If you're interested in more, all the presentations and workshop materials are available here >>
TensorFlow 2.0 is a major milestone that's expected to be released sometime soon. The main focus is usability and will include a variety of improvements that are highlighted here.
This repository contains a small Docker container for using R and TensorFlow as an enterprise REST API. This is from T-Mobile and it looks very well done. Includes great documentation and a permissive license.
This tutorial explores a variety of deep learning techniques for predicting stock price movements. It's a longread that covers a lot of ground but it's at a pretty high level that's easy to follow.
Mode Studio combines a SQL editor, Python & R notebooks, and a visualization builder in one platform. And it's free forever. Connect data from anywhere and analyze with the best language for the job, without having to jump between tools. Build custom visualizations or use our out-of-the-box charts. Share your analysis with a click—every report lives at a URL.
— Data Viz —
Follow the links for this "interactive experiment" from The Financial Times. It's a fantastic educational piece about reading charts.
The latest post from the Multiple Views blog shows how to handle measurement errors that are assumed to exist but aren't explicitly accounted for. "Implicit error" is related to uncertainty but it's not the same.
— Career —
The latest post from the Acing AI interview series focuses on interviewing at Airbnb. Includes an overview of their interview process, how the teams are structured, important reading, key links and sample questions. Regardless of which side of the interview table you might be on, this is a great series to pay attention to.