The evolution of GraphLab
Editor’s note: Carlos Guestrin will be part of the team teaching Large-scale Machine Learning Day at Strata + Hadoop World in San Jose. Visit the Strata + Hadoop World website for more information on...
View ArticleForecasting events, from disease outbreaks to sales to cancer research
Editor’s note: One of the more popular speakers at Strata + Hadoop World, Kira Radinsky was recently profiled in the new O’Reilly Radar report, Women in Data: Cutting-Edge Practitioners and Their Views...
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Topic models: Past, present, and future
I don’t remember when I first came across topic models, but I do remember being an early proponent of them in industry. I came to appreciate how useful they were for exploring and navigating large...
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Turning Ph.D.s into industrial data scientists and data engineers
Editor’s note: The ASI will offer a two-day intensive course, Practical Machine Learning, at Strata + Hadoop World in London in May. Back when I was considering leaving academia, the popular exit...
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Redefining power distribution using big data
When I first hear of a new open source project that might help me solve a problem, the first thing I do is ask around to see if any of my friends have tested it. Sometimes, however, the early...
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Building big data systems in academia and industry
Mikio Braun is a machine learning researcher who also enjoys software engineering. We first met when he co-founded a real-time analytics company called streamdrill. Since then, I’ve always had great...
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Coming full circle with Bigtable and HBase
Subscribe to the O’Reilly Data Show to explore the opportunities and techniques driving big data and data science. At least once a year, I sit down with Michael Stack, engineer at Cloudera, to get an...
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The tensor renaissance in data science
After sitting in on UC Irvine Professor Anima Anandkumar’s Strata + Hadoop World 2015 in San Jose presentation, I wrote a post urging the data community to build tensor decomposition libraries for...
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Data science makes an impact on Wall Street
Request an invitation to Next:Money, O’Reilly’s conference focused on the fundamental transformation taking place in the finance industry. Having started my career in industry, working on problems in...
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Apache Spark: Powering applications on-premise and in the cloud
As organizations shift their focus toward building analytic applications, many are relying on components from the Apache Spark ecosystem. I began pointing this out in advance of the first Spark Summit...
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Building self-service tools to monitor high-volume time-series data
One of the main sources of real-time data processing tools is IT operations. In fact, a previous post I wrote on the re-emergence of real-time, was to a large extent prompted by my discussions with...
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Why data preparation frameworks rely on human-in-the-loop systems
As I’ve written in previous posts, data preparation and data enrichment are exciting areas for entrepreneurs, investors, and researchers. Startups like Trifacta, Tamr, Paxata, Alteryx, and CrowdFlower...
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6 reasons why I like KeystoneML
As we put the finishing touches on what promises to be another outstanding Hardcore Data Science Day at Strata + Hadoop World in New York, I sat down with my co-organizer Ben Recht for the the latest...
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Understanding neural function and virtual reality
Like many data scientists, I’m excited about advances in large-scale machine learning, particularly recent success stories in computer vision and speech recognition. But I’m also cognizant of the fact...
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Pattern recognition and sports data
Sign-up now to receive a free download of the new O’Reilly report “Data Analytics in Sports: How Playing with Data Transforms the Game” when it publishes this fall. Julien Vervaecke and Maurice Geldhof...
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Bridging the divide: Business users and machine learning experts
Subscribe to the O’Reilly Data Show Podcast to explore the opportunities and techniques driving big data and data science. As tools for advanced analytics become more accessible, data scientist’s roles...
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Resolving transactional access and analytic performance trade-offs
Subscribe to the O’Reilly Data Show Podcast to explore the opportunities and techniques driving big data and data science. In recent months, I’ve been hearing about hybrid systems designed to handle...
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Turning big data into actionable insights
Subscribe to the O’Reilly Data Show Podcast to explore the opportunities and techniques driving big data and data science. Can developments in data science and big data infrastructure drive corporate...
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Graph databases are powering mission-critical applications
Subscribe to the O’Reilly Data Show Podcast to explore the opportunities and techniques driving big data and data science. While most people associate graphs with social media analysis, there are a...
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Building a scalable platform for streaming updates and analytics
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 sit down with Evan Chan,...
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