[A version of this post appears on the O’Reilly Radar.] The O’Reilly Data Show Podcast: Geoffrey Bradway on building a trading system that synthesizes many different models. Subscribe to the O’Reilly Data Show Podcast to explore the opportunities and techniques driving big data, data science, and AI. Find us on Stitcher, TuneIn, iTunes, SoundCloud, RSS.Continue reading “Programming collective intelligence for financial trading”
Tag Archives: crowdsourcing
Data preparation in the age of deep learning
[A version of this post appears on the O’Reilly Radar.] The O’Reilly Data Show Podcast: Lukas Biewald on why companies are spending millions of dollars on labeled data sets. Subscribe to the O’Reilly Data Show Podcast to explore the opportunities and techniques driving big data, data science, and AI. Find us on Stitcher, TuneIn, iTunes,Continue reading “Data preparation in the age of deep learning”
Building a business that combines human experts and data science
The O’Reilly Data Show podcast: Eric Colson on algorithms, human computation, and building data science teams. [A version of this post appears on the O’Reilly Radar.] Subscribe to the O’Reilly Data Show Podcast to explore the opportunities and techniques driving big data and data science. In this episode of the O’Reilly Data Show, I spokeContinue reading “Building a business that combines human experts and data science”
“Humans-in-the-loop” machine learning systems
Next week I’ll be hosting a webcast featuring Adam Marcus, one of the foremost experts on the topic of “humans-in-the-loop” machine learning systems. It’s a subject many data scientists have heard about, but very few have had the experience of building productions systems that leverage humans: Crowdsourcing marketplaces like Elance-oDesk or CrowdFlower give us accessContinue reading ““Humans-in-the-loop” machine learning systems”
Real-world Active Learning
Beyond building training sets for machine-learning, crowdsourcing is being used to enhance the results of machine-learning models: in active learning, humans take care of uncertain cases, models handle the routine ones. Active Learning is one of those topics that many data scientists have heard of, few have tried, and a small handful know how toContinue reading “Real-world Active Learning”
Crowdsourcing Feature discovery
More than algorithms, companies gain access to models that incorporate ideas generated by teams of data scientists [A version of this post appears on the O’Reilly Data blog and Forbes.] Data scientists were among the earliest and most enthusiastic users of crowdsourcing services. Lukas Biewald noted in a recent talk that one of the reasonsContinue reading “Crowdsourcing Feature discovery”