[A version of this article appears on the O’Reilly Radar.] The O’Reilly Data Show podcast: Dean Wampler on bounded and unbounded data processing and analytics. Subscribe to the O’Reilly Data Show Podcast to explore the opportunities and techniques driving big data and data science. I first found myself having to learn Scala when I startedContinue reading “Building enterprise data applications with open source components”
Tag Archives: podcast
From search to distributed computing to large-scale information extraction
Subscribe to the O’Reilly Data Show Podcast to explore the opportunities and techniques driving big data and data science. February 2016 marks the 10th anniversary of Hadoop — at a point in time when many IT organizations actively use Hadoop, and/or one of the open source, big data projects that originated after, and in someContinue reading “From search to distributed computing to large-scale information extraction”
Bridging the divide: Business users and machine learning experts
[A version of this articles 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. As tools for advanced analytics become more accessible, data scientist’s roles will evolve. Most media stories emphasize a need for expertise in algorithms and quantitative techniquesContinue reading “Bridging the divide: Business users and machine learning experts”
Understanding neural function and virtual reality
[A version of this article appears on the O’Reilly Radar.] The O’Reilly Data Show Podcast: Poppy Crum explains that what matters is efficiency in identifying and emphasizing relevant data. 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 cognizantContinue reading “Understanding neural function and virtual reality”
6 reasons why I like KeystoneML
[A version of this article appears on the O’Reilly Radar.] The O’Reilly Data Show Podcast: Ben Recht on optimization, compressed sensing, and large-scale machine learning pipelines. 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 withContinue reading “6 reasons why I like KeystoneML”
Why data preparation frameworks rely on human-in-the-loop systems
[A version of this article appears on the O’Reilly Radar.] 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 continue to innovate and attract enterprise customers. I’ve also noticed that companies — that don’t specialize in theseContinue reading “Why data preparation frameworks rely on human-in-the-loop systems”
Building self-service tools to monitor high-volume time-series data
[A version of this post appears on the O’Reilly Radar.] The O’Reilly Data Show Podcast: Phil Liu on the evolution of metric monitoring tools and cloud computing. 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 aContinue reading “Building self-service tools to monitor high-volume time-series data”
Apache Spark: Powering applications on-premise and in the cloud
[A version of this post appears on the O’Reilly Radar.] 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 in 2013 and since then, Spark adoption has exploded. With Spark Summit SF rightContinue reading “Apache Spark: Powering applications on-premise and in the cloud”
Data science makes an impact on Wall Street
[A version of this article appears on the O’Reilly Radar.] Having started my career in industry, working on problems in finance, I’ve always appreciated how challenging it is to build consistently profitable systems in this extremely competitive domain. When I served as quant at a hedge fund in the late 1990s and early 2000s, IContinue reading “Data science makes an impact on Wall Street”
The tensor renaissance in data science
[A version of this post appears on the O’Reilly Radar.] The O’Reilly Data Show Podcast: Anima Anandkumar on tensor decomposition techniques for machine learning. 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 forContinue reading “The tensor renaissance in data science”