Getting Started in Machine Learning AMA
By James McClain, Rob Emanuele and Lewis Fishgold on January 29th, 2020
3 of our machine learning engineers answer your questions about getting started with machine learning.
Building Footprint Comparison in Cambodia: Orbital Insight and OpenStreetMap
By Ross Bernet and Andrew Fink-Miller on January 23rd, 2020
We created a map that shows the difference between two building footprint datasets of Cambodia: OSM and Orbital Insights' AI generated dataset.
3 Ways to Analyze the Results of a Supervised Machine Learning Model
By Joe Morrison on December 13th, 2019
How accurate are our supervised machine learning models and what are they really doing? We offer 3 tips to help you better understand these models.
Modeling State with TypeScript
By Peter Caisse on December 12th, 2019
Working with frontend state can be challenging. With TypeScript, thoughtfully constructed types can help prevent bugs by making bad states unrepresentable. Let's explore a common use case and examine how to do this effectively in TypeScript.
Ethical Machine Learning for Disaster Relief: Rage for Machine Learning
By Niki LaGrone on December 10th, 2019
ML's predictive powers are driving a rage for deep learning in the crisis management and disaster relief industries. How can these powers be harnessed for ethical machine learning?
Ethical Machine Learning for Disaster Relief: Avoiding the Second Disaster
By Niki LaGrone on November 25th, 2019
Machine learning on satellite imagery is revolutionizing disaster relief. What does ethical machine learning mean in this field?