Competition posts
Explore the latest in our mission to build a better world using data science and AI.
Explore the latest in our mission to build a better world using data science and AI.
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!
We'll show you how to tune a U-Net model to measure flood extent using Sentinel-1 synthetic-aperture radar imagery.
In this post, we will introduce the Facebook AI Image Similarity Challenge and highlight some resources to help you get started.
Learn how these top teams built the most accurate ways to privatize millions of taxi rides.
We'll show you how to get started with the residual U-NET benchmark model, a state-of-the-art approach to predicting the height and pose of ground objects for monocular satellite images taken from oblique angles.
Meet the winners who were best able to predict disturbances in Earth's magnetic field, and hear them explain their creative solutions.
Learn how these top teams built the most accurate ways to privatize census records.
Meet the winners who were best able to estimate the wind speeds of tropical storms at different points in time using satellite images.
Check out the winning solutions to identify the lab-of-origin for genetically engineered DNA, and meet their leaderboard-topping creators.
Hear from the winners who were best able to detect hate speech in memes using multi-modal models.
Hear how these top teams built the most accurate ways to privatize emergency call data in Baltimore.
We'll show you how to train an LSTM network using space weather data to predict changes in Earth's magnetic field for our latest challenge.
We'll show you how to start predicting wind speeds for our latest disaster preparedness challenge.
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