Blogs

The power of machine learning in Spark

The power of machine learning in Spark

June 13, 2016 | by Max Seiden, Lead Spark Engineer, Platfora
Spark’s built-in machine-learning library (MLlib) provides a key differentiator from predecessor open source technologies and leverages Spark’s distributed, in-memory execution model. Take a look at some practical applications for specific Spark machine-learning algorithms in three advanced...
How can data scientists collaborate to build business applications?

How can data scientists collaborate to build better business applications?

June 10, 2016 | by James Kobielus, Big Data Evangelist, IBM
We asked five social influencers how data scientists can collaborate to build better business applications. See what they had to say.
InsightOut: The role of Apache Atlas in the open metadata ecosystem

InsightOut: The role of Apache Atlas in the open metadata ecosystem

Frameworks for open metadata and governance

June 10, 2016 | by Mandy Chessell, Distinguished Engineer, IBM Analytics Group CTO Office, IBM
What makes Apache Atlas different from other metadata solutions is that it is designed to ship with the platform where the data is stored. It is, in fact, a core component of the data platform.
Top analytics tools in 2016

Top analytics tools in 2016

June 10, 2016 | by Gaurav Vohra, CEO & Co-Founder, Jigsaw Academy, The Online School of Analytics
Join us for a look at what’s on the horizon in data analytics, discovering how a broad array of tools aims to change the way we do—and think about—data science.
End-to-end analytics in the cloud

End-to-end analytics in the cloud

June 9, 2016 | by John J. Thomas, Distinguished Engineer and Director, IBM Competitive Project Office, IBM
Deriving actionable insight from data and analytics is shifting to unified, cloud-based platforms that can be used by a variety of analysis personas. Take a look at a national retail chain scenario demonstrating how a comprehensive portfolio of end-to-end analytics in the cloud can provide the...
Highlights from the Apache Spark Maker Community Event

Highlights from the Apache Spark Maker Community Event

June 8, 2016 | by James Kobielus, Big Data Evangelist, IBM
Stay on the cutting edge with these highlights from the Apache Spark Maker Community Event as you sit in on interviews with industry leaders and explore the power of the IBM Data Science Experience.
Experiencing deeper productivity in open data science

Experiencing deeper productivity in open data science

June 7, 2016 | by James Kobielus, Big Data Evangelist, IBM
Reimagine the data science experience as an open experience with this IDE, which aims to facilitate a full range of development tasks, from data acquisition and data mining to prototyping and programming. When you do, discover how you can use Apache Spark and R to pursue open analytics by building...
Improving quality of life with Spark-empowered machine learning

Improving quality of life with Spark-empowered machine learning

June 2, 2016 | by Michal Malohlava, Software Engineer, H2O.ai
Machine learning is finding its way into a variety of applications. Discover an open source machine learning platform that combines the data processing power of Spark with powerful machine learning algorithms courtesy of the H2O platform to tackle challenges technologists face when applying machine...
Learning to fly: How to predict flight delays using Spark MLlib

Learning to fly: How to predict flight delays using Spark MLlib

June 2, 2016 | by David Taieb, Architect, IBM Cloud Data Services, IBM
Flight delays because of weather are inevitable for frequent flyers and infrequent travelers alike. Fortunately, we are living in an era in which applications such as the flight predictor app can be quickly and cost-effectively designed, built and tested to stay abreast of useful information for...
Innovative business applications: The disruptive potential of open data science

Innovative business applications: The disruptive potential of open data science

June 1, 2016 | by James Kobielus, Big Data Evangelist, IBM
A world that grows increasingly complex calls for disruptive innovation in an open, collaborative environment. See how open data science provides an ecosystem of expertise, skill sets and advanced open source data science tools that fuels collaborative creativity in the development and deployment...

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