Technical posts

Meet the winners of the Where's Whale-do challenge, and learn about the deep learning models they developed to identify individual Cook Inlet beluga whales from images.

Meet the participants who built the best models for predicting airport configurations for 10 U.S. airports! Understanding the complex interactions between air traffic, weather, and airspace operations can help make air travel more smooth and efficient for everyone.

Classification algorithms give us a lower bound on how well we can distinguish categories; maybe machine learning competitions give us a way to estimate an upper bound.

Classification algorithms give us a lower bound on how well we can distinguish categories; maybe machine learning competitions give us a way to estimate an upper bound.

Meet the competitors who topped the leaderboards in the NASA Airathon challenge. Their predictions of surface-level air pollution could give millions of people the information required to protect their health.

Meet the minds behind the top models for identifying the chemical composition of planetary soil samples using mass spectrometry! Identifying the compounds within such samples can help scientists understand the past habitability of Mars.

How to get started with the Where's Whale-do beluga photo-identification challenge!

Better identifying and removing clouds from satellite imagery enables a wide variety of environmental applications in disaster recovery, conservation, and more. Get to know the winning participants who advanced state-of-the-art methods in cloud detection!

We'll show you how to get started identifying animal species from camera trap images!

We'll show you how to preprocess HDF5 files and work with an OMI NO2 data product to estimate air quality around the world!

We'll show you how to preprocess HDF4 files and work with a MAIAC AOD data product to estimate air quality around the world!

In this post, we will show you how to get started on analyzing mass spectrometry data collected for Mars exploration.

Meet the minds behind the top models for measuring wildlife depth! Accurate depth estimations help ecologists track wildlife populations and protect the ecosystems that depend on them.

Start exploring how to help airports manage their runways to keep air traffic flowing.

Introducing the winners of the Facebook AI Image Similarity Challenge! Meet the top teams who matched manipulated images with their source images.

We'll demonstrate how to get started predicting cloud cover in satellite imagery for our new competition!

Meet the winners who were best able to detect floodwater using synthetic-aperture radar (SAR) imagery! These winners developed solutions that can help to strengthen early warning systems and direct emergency relief.

Meet the winners with the best models for mapping oblique satellite imagery to geocentric pose! These winners helped made overhead imagery more useful for time-sensitive applications like emergency response.

Code execution competitions allow participants to run their code on unseen test sets and have their best scores displayed on a live leaderboard. Read on to learn more about the what, why, and how of DrivenData code execution competitions!