Is This a Crosswalk?: 5 Takeaways from Training a Data Labeling Team
By Niki LaGrone on September 13th, 2019
We trained remote computer vision workers to provide data labeling for machine learning projects. Here's what we learned.
Putting Native American Voters on the Map: Using Cadastral Data to Geocode Non-Traditional Addresses
By Fay Walker on September 12th, 2019
We used cadastral land survey data to geocode previously unmappable Native American voters in Montana.
Transfer Learning from RGB to Multi-band Imagery
By Adeel Hassan on August 30th, 2019
We used transfer learning to teach a model to take advantage of multi-band imagery without discarding the original RGB pre-training. This resulted in significant performance improvement.
Using the Dedupe Machine Learning Library for Cleaning and Matching Data
By Justin Walgran on August 30th, 2019
To deal with issues of apparel facility list data quality and scale quickly and efficiently we need a machine learning tool that can capture the knowledge of domain experts, find commonalities in jumbled text, and confidently compare large lists without the need to compare each individual entry.
Temperate Takes a Rural Approach
By Jessica Cahail on August 27th, 2019
Temperate will soon incorporate rural areas into its climate planning capabilities.
Connecting Data and People with the Open Apparel Registry
By Deb Boyer on August 7th, 2019
Since its launch on March 28, the Open Apparel Registry (OAR) has grown to include over 18,300 facilities in 92 countries. We’ve already heard of a few fascinating use cases where data from the OAR contributed to decision making by brands and facilities.