Welcome back to the round-up, an overview of the most interesting data science, statistics, and analytics articles of the past week. This week, we have 4 fascinating articles ranging in topics from computer vision to popular R packages. In this week's round-up:
- Google Explains How AI Photo Search Works
- Matter Over Mind in Machine Learning
- Principles of ML Benchmarking
- A List of R Packages, By Popularity
This is an interesting blog post about how Google recently enhanced their image search functionality using computer vision and machine learning algorithms. The post describes in layman's terms how the algorithms work and how they are able to classify pictures. It also includes a link to Google's research blog, where they made the original announcement.
This is a post on the BigML blog which talks about the work of Dr. Kiri Wagstaff from NASA's Jet Propulsion Laboratory. The post highlights a specific paper of hers where she argues that instead of aiming for incremental abstract improvements in machine learning processes, we should be focused on attaining results that translate into a measurable impact for society at large. More detail is provided about what that means, the author plays a little devil's advocate, and the post also includes a link to Wagstaff's paper for those that would like to read more about this.
This is a post on the Wise.io blog about how to benchmark machine learning algorithms. The post is structured as a thought exercise where the author starts by thinking about the purpose of benchmarking, why we should do it, and what our goals should be. From that point, he is able to formulate a set of guidelines for benchmarking that are very logical. The post lists each of the guiding principles along with some steps that can be taken to make sure you are abiding by them.
Our last article this week is a post on the Revolution Analyitcs blog that lists the top R packages in order of popularity. Some of the most popular packages include plyr, digest, ggplot2, and colorspace. Check out the list, see where your favorite packages rank, and potentially discover some useful packages you didn't know about!
That's it for this week. Make sure to come back next week when we’ll have some more interesting articles! If there's something we missed, feel free to let us know in the comments below.