This Week in Machine Learning, 5 August 2016

This week’s top Machine Learning stories, including bot control, crop yields, Autism gene correlations, and more!

Machine Learning is one of the most exciting fields in the world. Every week we discover something new, something amazing, something revolutionary. It’s incredible, but it can also be overwhelming. That’s why we created This Week in Machine Learning! Each week we publish a curated list of Machine Learning stories as a resource to help you keep pace with all these exciting developments. New posts will be published here first, and previous posts are archived on the Udacity blog.

Whether you’re currently enrolled in our Machine Learning Nanodegree program, already working in the field, or just pursuing a burgeoning interest in the subject, there will always be something here to inspire you!


Dataiku releases a new version of its Data Science Studio which supplies “visual machine learning”, allowing users to build predictive models with no programming ability.


New Mexico-based Descartes Labs uses machine learning on satellite imagery to predict crop yields with greater efficiency and accuracy than the USDA’s traditional method.

Law Enforcement

North Carolina’s Charlotte-Mecklenburg Police Department pilot tests a new machine learning method for identifying officers at risk of initiating adverse events from staff records.


Scientists at Princeton University use machine learning to speed up the rate at which we can identify genes that correlate with the presence of Autism spectrum disorder.

Commerce applies machine learning methods to traditional sales operations, compiling a “playbook” for more effective and efficient sales pitches for representatives.


Distil Networks uses machine learning algorithms to begin to defend against Advanced Persistent Bots, bots whose interactions are difficult to discern from real human users.