LABSBlog
Mapping Disaster Risk from Aerial Imagery - Benchmark
In this post we'll show you how to start working with aerial imagery to classify the roof material of buildings in St. Lucia, Guatemala, and Colombia.
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Richter's Predictor - Benchmark
In this post we'll show you how to start using data science to predict the extent of earthquake damage!
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Our Minimum Viable Process for changing and deploying software
Over the years, we have gradually settled on a process for changing and releasing software that is robust enough to prevent common failure modes but lightweight enough to be minimally annoying. Here’s what it looks like when we make a change.
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Meet the winners of Sustainable Industry: Rinse Over Run
Meet the winners who were best able to predict cleanliness levels and draw insights for more sustainable industrial practices!
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Sustainable Industry: Rinse Over Run - Benchmark
We're really excited to launch our latest competition! In addition to an interesting, new prize structure, the subject matter is at the intersection of sustainability and industry. Improvements to these kinds of processes can have upside for both a business and the planet.
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Meet the winners of Power Laws: Cold Start Energy Forecasting
Meet the winners who were best able to tackle the cold start problem in energy forecasting!
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DrivenData On The Air: Of Checklists, Ethics, and Data
Emily Dorne and Peter Bull discuss project deon on Podcast.init!
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How to Use an LSTM for Timeseries and the Cold-start Problem
We show you how to get a warm start on our cold start competition using a neural network!
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Machine Learning With A Heart - Benchmark
We've all got to start somewhere. In this post we'll show you how to start using data science to predict heart health!
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Results from Pri-Matrix Factorization and a New Open Source Tool for Wildlife Research and Conservation
Using AI to study the natural world: check out the results!
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Meet the winners of Power Laws: Anomaly Detection
Meet the winners who were best able to use machine learning to detect anomalies in building energy consumption!
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Meet the winners of the Power Laws: Forecasting Energy Consumption
Meet the winners who were best able to use machine learning to predict building energy consumption!
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Meet the winners of Power Laws: Optimizing Demand-side Strategies
Meet the winners who were best able to optimize energy use with a photovoltaic array and battery system!
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Meet the winners of the Pover-T Tests challenge
See how DrivenData's top modelers managed to predict poverty based on individual and household-level survey data.
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Five Finalists Announced to Uncover Emerging Biothreats
Meet the newly announced finalists in the Hidden Signals Challenge! This is a guest post from our friends at Luminary Labs.
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Concept To Clinic tools highlight: Travis CI
Continuous integration is a best practice for software development. We think it's a best practice for data science, too.
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Concept To Clinic tools highlight: FOSSA
Complying with open source licenses is difficult. Today we're talking about a tool that has made it easier for the Concept to Clinic challenge.
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A brief introduction to machine learning and 3 ways to make it useful for social impact organizations
When social sector organizations think about data, the conversation often begins and ends with measuring impact. Here are some ways that social impact organizations can move beyond thinking about measuring impact and start using machine learning to transform how they operate.
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Meet the winners of the N+1 Fish, N+2 Fish challenge
See how DrivenData's top modelers managed to predict length, species, and count from videos of fish captured on fishing vessels.
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Benchmark for Pover-T Test - Predicting Poverty
We're launching a new competition to predict poverty. In this post, we'll show you how to get started!
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