Blog


Meet the Final Winners of the U.S. PETs Prize Challenge

Learn how these top teams applied novel privacy-enhancing technologies to the problems of financial crime and pandemic forecasting.

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Meet the BioMassters

Meet the minds behind the top models for predicting aboveground biomass using remote sensing data!

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VisioMel Challenge: Predicting Melanoma Relapse - Benchmark

Get started with the VisioMel Challenge! Come up with the best algorithms for predicting melanoma relapse.

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The Basics of Python Packaging in Early 2023

Explaining the basic concepts and best practices for creating Python packages in early 2023 using pyproject.toml build standards.

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Pushback to the Future: Predict Pushback Time at US Airports - Benchmark

Get started with the Pushback to the Future challenge! Come up with the best algorithms for predicting a flight's pushback time from real-time flight data.

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What's a takahē?

Although Zamba's models are trained with animals from Africa and Europe, they can be used with videos from other locations that show species the models have never seen. We demonstrate with a dataset from New Zealand.

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Meet the winners of the Mars Spectrometry 2: Gas Chromatography Challenge

Meet the minds behind the top models for identifying the chemical composition of planetary soil samples using gas chromatography-mass spectrometry!

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How to Predict Harmful Algal Blooms Using LightGBM and Satellite Imagery

We'll show how to use satellite imagery and LightGBM to create a tree-based model predicting harmful algal blooms. This post will help you get started on our new Tick Tick Bloom Challenge!

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Standing on the Threshold

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?

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Getting started with the Meta AI Video Similarity Challenge

In this post, we walk through the steps for getting started with the Meta AI Video Similarity Challenge.

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Meet the Winners of the U.S. PETs Prize Challenge: Phase 1

Hear how these top teams applied novel privacy-enhancing technologies to the problems of financial crime and pandemic forecasting.

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Find all the pangolins

We can use Zamba's probablistic classifications to search for videos containing specific animals. Particularly for small animals, this strategy can be highly effective.

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The BioMassters Challenge - Benchmark

In this guest post by MathWorks, we'll show you how to start working with satellite data to help conservationists predict above ground biomass.

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You can stop watching blank videos

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.

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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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