LABSBlog
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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Bridging the AI application gap
The focus of the Concept to Clinic challenge is to make AI advances useful — not just for data scientists interested in cutting-edge methods, but for clinicians working on the front lines of lung cancer detection and the patients they serve.
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Interview with Concept to Clinic panelist Dr. Jason Hostetter
We interview Concept to Clinic panelist Dr. Jason Hostetter
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Interview with Concept to Clinic contributor Serhiy Shekhovtsov (@Serhiy-Shekhovtsov)
We interview Concept to Clinic challenge contributor Serhiy Shekhovtsov (@Serhiy-Shekhovtsov)
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Hidden Signals Challenge: can you help identify biothreats in real time?
Can you help identify biothreats in real time? Submit a concept by 12/4/17!
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Pri-matrix Factorization - Benchmark
How about some deep learning to identify wild animals in camera traps? Here's a benchmark post to get contributors started in our newest challenge.
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How the Concept to Clinic challenge uses Docker for reproducibility and orchestration
Ensuring easy setup of the application stack and efficient segmentation of the various components of the Concept to Clinic challenge is precisely where Docker excels, especially when used with Docker Compose, its tool for declaring and orchestrating multiple services. In this post, we'll dive into some background on Docker and explain how we're using it in the Concept to Clinic challenge.
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Interview with Concept to Clinic contributor Willi Gierke (@WGierke)
We had an e-chat to learn more about prolific Concept to Clinic challenge contributor Willi Gierke (@WGierke)
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Random walk of the penguins
The goal of this data science competition was to reach out to the data science community to build a model that predicts penguin populations.
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