This Week in Machine Learning, 6 May 2016
This week’s top Machine Learning stories, including Uber’s plans to phase out surge pricing, a new predictive engine from Seattle, 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!
Uber announces plans to use machine learning to phase out its surge pricing by predicting high-traffic areas and proactively redirecting drivers.
Researchers from Microsoft debut CryptoNets, neural networks that can work on sensitive encrypted data in fields like healthcare, education, and finance.
Zooniverse tests the Planetary Response Network (PRN) on the earthquake in Ecuador, rapidly identifying damaged areas and allocating emergency personnel accordingly.
Material scientists leverage machine learning to generate and test theoretical materials by learning from the crystal structures of existing materials.
Scientists from the Israel Institute of Technology publish an investigation of Deep Q-networks, revealing their success lies in hierarchical aggregations of the state space.
Seattle-based Textio debuts Opportunities, a new predictive engine that helps companies identify and correct male-oriented language in job postings.