Blog


Computer Vision for Wildlife Monitoring in a Changing Climate

Through the Patrick J. McGovern Foundation Accelerator, DrivenData and the Wild Chimpanzee Foundation are teaming up to create automated, accurate, and accessible species detection tools.

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Mars Spectrometry 2: Gas Chromatography - Benchmark

In this post, we will show you how to get started on analyzing gas chromatography-mass spectrometry (GCMS) data.

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Meet the winners of the Snowcast Showdown competition

Meet the winners who most accurately estimated snow water equivalent across the Western U.S. in real-time.

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Meet the winners of the Where's Whale-do Challenge

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.

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Meet the winners of the Run-way Functions Challenge

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.

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How Classifiable Is It? (Part 2)

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.

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How Classifiable Is It? (Part 1)

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.

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Meet the winners of the NASA Airathon: Predict Air Quality Challenge

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.

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Meet the winners of the Mars Spectrometry Challenge

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.

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Where's Whale-Do? Data Exploration and Benchmark

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

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Meet the winners of the Cloud Cover Detection 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!

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Introduction to Image Classification using Camera Trap Images

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

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Happy April Fools' Day from DrivenData (and our pets)

Hear from the DrivenPets about the results of our competition on the pet-productivity connection for remote workers

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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!

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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!

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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.

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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.

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Run-way Functions: Predict Reconfigurations at US Airports - Benchmark

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

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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.

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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!

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