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Youth Mental Health Narratives
Help advance youth suicide research by extracting information from narratives in the National Violent Death Reporting System. #health
Flu Shot Learning: Predict H1N1 and Seasonal Flu Vaccines
Can you predict whether people got H1N1 and seasonal flu vaccines using information they shared about their backgrounds, opinions, and health behaviors? #health
Richter's Predictor: Modeling Earthquake Damage
Can you predict the level of damage to buildings caused by the 2015 Gorkha earthquake in Nepal based on aspects of building location and construction? #disasters
DengAI: Predicting Disease Spread
Using environmental data collected by U.S. Federal Government agencies, can you predict the number of dengue fever cases reported each week in San Juan, Puerto Rico and Iquitos, Peru? #health
Pump it Up: Data Mining the Water Table
Can you predict which water pumps are faulty to promote access to clean, potable water across Tanzania? This is an intermediate-level practice competition. #development
Conser-vision Practice Area: Image Classification
Looking for a great way to start working with computer vision? This competition features a small dataset of wildlife captured by camera traps used in conservation research. #climate
Water Supply Forecast Rodeo
Water managers in the Western U.S. rely on accurate water supply forecasts to better operate facilities and mitigate drought. Help the Bureau of Reclamation improve seasonal water supply estimates in this probabilistic forecasting challenge! #climate
Pose Bowl: Spacecraft Detection and Pose Estimation Challenge
Develop object detection and pose estimation algorithms for use on inspector spacecraft. #science
SNOMED CT Entity Linking Challenge
Link spans of text in clinical notes to concepts in the SNOMED CT clinical terminology. #health
Kelp Wanted: Segmenting Kelp Forests
Help researchers estimate the extent of Giant Kelp Forests by segmenting Landsat imagery. #climate
PREPARE: Pioneering Research for Early Prediction of Alzheimer's and Related Dementias EUREKA Challenge
Help the NIH discover novel approaches for the early prediction of Alzheimer's disease and related dementias. #health
Pale Blue Dot: Visualization Challenge
Use public Earth observation data to create a visualization that furthers the Sustainable Development Goals of zero hunger, clean water and sanitation, or climate action. #development
Meta AI Video Similarity Challenge
Help keep social media safe by identifying whether a video contains a manipulated clip from one or more videos in a reference set. #society
Unsupervised Wisdom: Explore Medical Narratives on Older Adult Falls
Use unsupervised machine learning approaches to extract insights from emergency department narratives about how, when, and why older adults (age 65+) fall. #health
Research Rovers: AI Research Assistants for NASA
Help NASA assess emerging capabilities for AI-based research assistants. #science
Pushback to the Future: Predict Pushback Time at US Airports
Accurate estimates of pushback time can help air traffic management systems more efficiently use the limited capacity of airports, runways and the National Airspace System. Use air traffic and weather data to automatically predict pushback time! #civic
VisioMel Challenge: Predicting Melanoma Relapse
Use digitized microscopic slides to predict the likelihood of melanoma relapse within the next five years. #health
U.K. PETs Prize Challenge
Help unlock the potential of privacy-enhancing technologies (PETs) to combat global societal challenges. Develop efficient, accurate, and extensible federated learning solutions with strong privacy guarantees for individuals in the data. #privacy
U.S. PETs Prize Challenge
Help unlock the potential of privacy-enhancing technologies (PETs) to combat global societal challenges. Develop efficient, accurate, and extensible federated learning solutions with strong privacy guarantees for individuals in the data. #privacy
Tick Tick Bloom: Harmful Algal Bloom Detection Challenge
Harmful algal blooms occur all around the world, and can harm people, their pets, and marine life. Use satellite imagery to detect dangerous concentrations of cyanobacteria, and help protect public health! #climate
The BioMassters
Help conservationists make use of satellite imagery to estimate the aboveground biomass of Finnish forests. #climate
Mars Spectrometry 2: Gas Chromatography
Help NASA scientists identify the chemical composition of rock and soil samples for Mars planetary science. #science
Snowcast Showdown
Seasonal snowpack is a critical water resource throughout the Western U.S. Help the Bureau of Reclamation estimate snow water equivalent (SWE) at a high spatiotemporal resolution using near real-time data sources. #climate
Where's Whale-do?
Help the Bureau of Ocean Energy Management (BOEM), NOAA Fisheries, and Wild Me accurately identify endangered Cook Inlet beluga whales from photographic imagery. Scalable photo-identification of individuals is critical to population assessment, management, and protection for these endangered whales. #climate
Facebook AI Image Similarity Challenge
Advance the science of image similarity detection, with applications in areas including content tracing, copyright infringement and misinformation. #society
Run-way Functions: Predict Reconfigurations at US Airports
Air traffic managers monitor the skies and respond by changing the airport configuration. Tools that give flight operators early warning for upcoming changes can help streamline air travel and reduce delays. Use real-time data to predict future airport configurations. #civic
Mars Spectrometry: Detect Evidence for Past Habitability
Help NASA scientists identify the chemical composition of rock and soil samples for Mars planetary science. #science
NASA Airathon: Predict Air Quality
Air pollution is one of the greatest environmental threats to human health. Help NASA deliver accurate, high-resolution air quality information to improve public health and safety! #climate
On Cloud N: Cloud Cover Detection Challenge
Clouds obscure important ground-level features in satellite images, complicating their use in downstream applications. Build algorithms for cloud cover detection using a new cloud dataset and Microsoft's Planetary Computer! #science
Deep Chimpact: Depth Estimation for Wildlife Conservation
Help conservationists monitor wildlife populations. In this challenge, you will estimate the depth of animals in camera trap videos. Better distance estimation models can rapidly accelerate the availability of critical information for wildlife monitoring and conservation. #climate
STAC Overflow: Map Floodwater from Radar Imagery
Help Microsoft AI for Earth and Cloud to Street detect floodwater through cloud coverage using Sentinel-1 synthetic-aperture radar (SAR) imagery. Accurate flood mapping can save lives by strengthening early warning systems and directing emergency relief. #disasters
Overhead Geopose Challenge
Help make overhead imagery more useful for time-sensitive applications like disaster response. Build computer vision algorithms that can effectively model the height and pose of ground objects for monocular satellite images taken from oblique angles. #science
Differential Privacy Temporal Map Challenge
Help public safety agencies share data while protecting privacy. This is a series of contests to develop algorithms that preserve the usefulness of temporal map data while guaranteeing individual privacy is protected. #privacy
Hateful Memes
Detecting hateful content presents a unique challenge in memes, where multiple data modalities need to be analyzed together. Facebook is calling on researchers around the world to help identify which memes contain hate speech. #society
MagNet: Model the Geomagnetic Field
Help NOAA better forecast changes in Earth’s magnetic field! Improved models can provide more advanced warning of geomagnetic storms and reduce errors in magnetic navigation systems. #science
Wind-dependent Variables: Predict Wind Speeds of Tropical Storms
Throughout a tropical cyclone, humanitarian response efforts hinge on accurate storm intensity estimates. Using satellite images assembled by Radiant Earth Foundation and the NASA IMPACT team, can you estimate the wind speeds of storms at different times? #disasters
TissueNet: Detect Lesions in Cervical Biopsies
The objective of this challenge is to detect the most severe epithelial lesions of the uterine cervix. The challenge brings together thousands of microscopic slides from different medical centers across France. #health
Genetic Engineering Attribution Challenge
Genetic engineering is a powerful tool that demands responsible use. Your goal is to create an algorithm that identifies the lab-of-origin for genetically engineered DNA with the highest accuracy level possible. #science
Clog Loss: Advance Alzheimer’s Research with Stall Catchers
Help accelerate Alzheimer's research by automatically classifying which blood vessels are flowing and which are stalled. #health
Open Cities AI Challenge: Segmenting Buildings for Disaster Resilience
Can you map building footprints from drone imagery? This semantic segmentation challenge leverages computer vision and data from OpenStreetMap to support disaster risk management efforts in cities across Africa. #disasters
Hakuna Ma-data: Identify Wildlife on the Serengeti with AI for Earth
Can you predict which animals are present in camera trap images? Leverage millions of images of animals on the Serengeti to build a classifier that distinguishes between gazelles, lions, and more! #climate
Open AI Caribbean Challenge: Mapping Disaster Risk from Aerial Imagery
Can you predict the roof material of buildings from drone imagery? Leverage aerial imagery in St. Lucia, Guatemala, and Colombia to more accurately map disaster risk at scale. #disasters
Sustainable Industry: Rinse Over Run
Help make industrial cleaning processes more efficient! The goal of this competition is to predict measures of cleanliness during final rinse in order to help minimize the use of water, energy and time, all while ensuring high cleaning standards. #energy
Power Laws: Cold Start Energy Forecasting
Usually with buildings, bigger historic datasets yield more accurate consumption forecasts. The goal of this challenge is to provide an accurate forecast from the very beginning of the building instrumentation life, without much consumption history. #energy
Power Laws: Optimizing Demand-side Strategies
Storage is critical to flexible and reliable access to renewable energy sources. In this challenge, competitors combined traditional optimization methods and machine learning to build algorithms for controlling a battery charging system as efficiently as possible. #energy
Power Laws: Detecting Anomalies in Usage
Commercial buildings waste an estimated 15% to 30% of energy used due to poorly maintained, degraded, and improperly controlled equipment. Competitors built quick-response algorithms to find anomalies in energy use and elevate them for human attention and intervention. #energy
Power Laws: Forecasting Energy Consumption
More accurate forecasts of building energy consumption mean better planning and more efficient energy use. In this challenge, competitors used machine learning to build the most accurate predictions of the future from limited data in the past. #energy
Pover-T Tests: Predicting Poverty
Measuring poverty is hard. Thanks to the efforts of thousands of competitors, The World Bank can now build on open source machine learning tools to help predict poverty, optimize uses of survey data, and support work to end extreme poverty … #development
Pri-matrix Factorization
Data scientists from more than 90 countries around the world drew on 300,000 video clips in a competition to build the best machine learning models for identifying wildlife from camera trap footage. The results are powerful and – equally important … #climate
N+1 fish, N+2 fish
Sustainable fishing means tracking every fish caught. New tools using automated video processing and artificial intelligence can help responsible fisheries comply with regulations, save time, and lower the safety risk and cost from an auditor on board. #climate
Random Walk of the Penguins
Competitors built hundreds of algorithms to predict changes in Antarctic penguin populations from the most comprehensive counts available. These algorithms give researchers a greater understanding of penguin population dynamics, a leading indicator of climate change. #climate
America's Next Top (Statistical) Model
US presidential elections come but once every 4 years, and this one's a big one. There are lots of people trying to predict what will happen. Can you top them? #civic
Senior Data Science: Safe Aging with SPHERE
Contribute to open, cutting-edge research on the use of wearables in promoting health and independence for seniors. #health
From Fog Nets to Neural Nets
Model the water output from water-collecting fog nets in Southwest Morocco. Accurate predictions can improve collection efforts and enable greater access to fresh water throughout the year. #development
Naive Bees Classifier
Can you identify a bee as a honey bee or a bumble bee? Practice image processing and classification techniques and help researchers seeking to protect pollinators from collapse. #science
Keeping it Fresh: Predict Restaurant Inspections
Flag public health risks at restaurants by combining Yelp reviews with open city data on past inspections. An algorithmic approach discovers more violations with the same number of inspections. #civic
Countable Care: Modeling Women's Health Care Decisions
Can you predict what drives women’s health care decisions in America? In an uncertain health landscape, this survey modeling challenge can help illuminate what care people receive, where they go, and how they pay. #health
Box-Plots for Education
Tag school budgets automatically to help districts get a better grasp of their spending and how to improve the impact of their scarce resources. #education
Preview: The Future of DrivenData Competitions
Learn more about exciting upcoming changes to DrivenData's data science competitions.
Reboot: Box-Plots for Education
We're rebooting our first prized competition for fun and education! Tag school budgets automatically to help districts get a better grasp of their spending and how to improve the impact of their scarce resources. #education
Pawsitive Predictive Value: Pets and Productivity
Understanding the pet–productivity connection for workers is critical to sustained long-term economic growth. Can you predict DrivenData team members' productivity based on their proximity to their pets?
United Nations Millennium Development Goals
The UN's Millennium Development Goals provide the big-picture perspective on international development. Using indicators aggregated and collected by the World Bank, try to predict progress towards select MDGs. #development
America's Next Top (Statistical) Model - 2020
US presidential elections come but once every 4 years, and this one's a big one. There are lots of people trying to predict what will happen. Can you top them? #civic
Warm Up: Machine Learning with a Heart
Can you predict the presence or absence of heart disease in patients given basic medical information? This is the smallest, least complex dataset on DrivenData, and a great place to dive into the world of data science competitions. #health
Warm Up: Predict Blood Donations
Can you predict whether a donor will return to donate blood given their donation history? This is the smallest, least complex dataset on DrivenData, and a great place to dive into the world of data science competitions. #health