Tools and Techniques
Researchers recruited 61 analysts and asked them specific questions about the same set of data. What happened next suggests some worthwhile approaches for both small and large teams.
Continuation of a three part series that explores the massive landscape of tools that are available to data scientists. This week's focus: Data Wrangling - the necessary dirty work that's said to take up to 80% of data scientists' time.
A number of researchers have recently shown that Convolutional Networks can be easily fooled. This article is a good discussion of what's really going on and offers suggestions for moving forward.
Sentiment analysis is a type of Natural Language Processing that extracts subjective information, such as emotion, from text. This tutorial by District Data Labs provides a great overview of current strategies and how to work with two commonly used libraries: Word2Vec and Doc2Vec. Highly recommended.
Much of the analysis that used to be done with a traditional GIS can now be done in R. This is a good tutorial for getting started, using the raster and rasterVis packages by Oscar Perpiñán.