In the presentation below, courtesy of the SF Machine Learning Meetup group in San Francisco, Xiangrui Meng introduces Spark and show how to use it to build fast, end-to-end machine learning workflows.
IBM (NYSE: IBM) has announced the availability of a cognitive-infused Watson Explorer, a powerful combination of data exploration and content analytics capabilities. Watson Explorer equips users with the information and analytics capabilities which can help them to deliver better performance and real-time results.
In this presentation and interactive demo, you’ll learn about data mining workflows, the architecture and benefits of Spark, as well as practical use cases for the framework.
This article is the fifth and last in an editorial series that will provide direction for enterprise thought leaders on ways of leveraging in-memory computing to analyze data faster, improve the quality of business decisions, and use the insight to increase customer satisfaction and sales performance.
From the SciPy2013 conference, here is a compelling talk “Data Agnosticism: Feature Engineering Without Domain Expertise” by Nicholas Kridler of Accretive Health in Chicago.
This article is the fifth and last in an editorial series that has the goal to provide direction for enterprise thought leaders on ways of leveraging big data technologies in support of analytics proficiencies designed to work more independently and effectively in today’s climate of working to increase the value of corporate data assets.