Competition posts
Explore the latest in our mission to build a better world using data science and AI.
Content list
How to Estimate Surface-level NO2 using OMI Column NO2 Data
We'll show you how to preprocess HDF5 files and work with an OMI NO2 data product to estimate air quality around the world!
How to Predict PM2.5 using MAIAC Aerosol Optical Depth Data
We'll show you how to preprocess HDF4 files and work with a MAIAC AOD data product to estimate air quality around the world!
Mars Spectrometry: Detect Evidence for Past Habitability - Benchmark
In this post, we will show you how to get started on analyzing mass spectrometry data collected for Mars exploration.
Meet the winners of the Deep Chimpact: Depth Estimation for Wildlife Conservation Challenge
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.
Run-way Functions: Predict Reconfigurations at US Airports - Benchmark
Start exploring how to help airports manage their runways to keep air traffic flowing.
Meet the winners of the Image Similarity Challenge
Introducing the winners of the Facebook AI Image Similarity Challenge! Meet the top teams who matched manipulated images with their source images.
How to Use Deep Learning, PyTorch Lightning, and the Planetary Computer to Predict Cloud Cover in Satellite Imagery
We'll demonstrate how to get started predicting cloud cover in satellite imagery for our new competition!
Meet the winners of STAC Overflow: Map Floodwater from Radar Imagery Challenge
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.
Deep Chimpact: Depth Estimation for Wildlife Conservation - Benchmark
In this guest post by MathWorks, we'll show you how to start working with camera trap videos to estimate the distance to an animal seen in the wild.
Meet the winners of the Overhead Geopose Challenge
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.
A peek inside DrivenData's code execution competitions
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!
How to Map Floodwater from Radar Imagery using Semantic Segmentation - Benchmark
We'll show you how to tune a U-Net model to measure flood extent using Sentinel-1 synthetic-aperture radar imagery.
Facebook AI Image Similarity Challenge - Getting Started
In this post, we will introduce the Facebook AI Image Similarity Challenge and highlight some resources to help you get started.
Meet the Winners of the Differential Privacy Temporal Map Challenge: Sprint 3
Learn how these top teams built the most accurate ways to privatize millions of taxi rides.
Overhead Geopose Challenge - Benchmark
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 of MagNet: Model the Geomagnetic Field
Meet the winners who were best able to predict disturbances in Earth's magnetic field, and hear them explain their creative solutions.
Meet the Winners of the Differential Privacy Temporal Map Challenge: Sprint 2
Learn how these top teams built the most accurate ways to privatize census records.
Meet the winners of Wind-dependent Variables: Predict Wind Speeds of Tropical Storms
Meet the winners who were best able to estimate the wind speeds of tropical storms at different points in time using satellite images.
Meet the winners of the Genetic Engineering Attribution Challenge
Check out the winning solutions to identify the lab-of-origin for genetically engineered DNA, and meet their leaderboard-topping creators.
Meet the winners of the Hateful Memes Challenge
Hear from the winners who were best able to detect hate speech in memes using multi-modal models.
Meet the Winners of the Differential Privacy Temporal Map Challenge: Sprint 1
Hear how these top teams built the most accurate ways to privatize emergency call data in Baltimore.
How to Predict Disturbances in the Geomagentic Field with LSTMs - Benchmark
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.
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