DrivenData blog
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.
Using probabilistic classifications from Zamba, we can automatically remove a large majority of blank videos while controlling the fraction of wildlife videos we lose. But how do we know where to draw the line?
In this post, we walk through the steps for getting started with the Meta AI Video Similarity Challenge.
Hear how these top teams applied novel privacy-enhancing technologies to the problems of financial crime and pandemic forecasting.
We can use Zamba's probablistic classifications to search for videos containing specific animals. Particularly for small animals, this strategy can be highly effective.
Using Zamba's probablistic classifications, you can identify and remove blank videos -- saving viewing time, storage space, and data transfer costs -- while minimizing the loss of videos that contain animals.
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.
In this post, we will show you how to get started on analyzing gas chromatography-mass spectrometry (GCMS) data.
Meet the winners who most accurately estimated snow water equivalent across the Western U.S. in real-time.
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!
Hear from the DrivenPets about the results of our competition on the pet-productivity connection for remote workers
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.
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