This Week in Machine Learning, 16 September 2016

This week’s top Machine Learning stories! How Grand Theft Auto helps train self-driving cars, emotional intelligence algorithms, 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!


Israeli pharmaceutical firm Teva develops a machine learning platform informed by wearable devices to help research and treat Huntington’s disease.


A new machine learning system from UT Austin and Cornell University can identify the content of heavily blurred images of faces with significant accuracy and confidence.


A team of engineers from China’s Tsinghua University uses reinforcement learning to devise the ideal signaling patterns for complex traffic intersections.


Research groups use the popular Grand Theft Auto game franchise to train computer vision algorithms to be used in real-world self-driving cars.


California-based PowerScout leverages machine learning and available data to contact consumers most likely to benefit from installing solar panels.


Affectiva, makers of emotion-detection software powered by machine learning, predicts that one day, all devices will be equipped with emotional intelligence.