Get fresh updates from Hortonworks by email

Once a month, receive latest insights, trends, analytics information and knowledge of Big Data.


Get Started


Ready to Get Started?

Download sandbox

How can we help you?

closeClose button
September 09, 2014
prev slideNext slide

Hadoop’s Advantages for Machine Learning and Predictive Analytics

What drives successful implementations of big data analytics projects? Hortonworks’ Director of Data Science,

Ofer Mendelevitch, Director of Data Science,  Hortonworks
Ofer Mendelevitch, Director of Data Science, Hortonworks

Ofer Mendelevitch, teams up with Zementis’ Founder and CEO Michael Zeller to discuss their learnings from working with dozens of companies from small cloud-based start-ups to some of the largest companies in the world.

Register here for the webinar on September 10 at 10am Pacific Time.

Hortonworks will present their approach to using Apache Hadoop for predictive models with big data, and the benefits of Hadoop to data scientists. Zementis will demonstrate how to quickly deploy, execute, and optimize predictive models from open source machine learning tools like R and Python as well as commercial data mining vendors like IBM, SAP and SAS. Zementis leverages the PMML open industry standard (Predictive Model Markup Language) providing a higher ROI for big data and predictive analytics initiatives. At the same time reducing IT costs, and improving the quality of predictive model management while requiring no change in how data science teams do their day-to-day work.

Michael Zeller, Founder and CEO, Zementis
Michael Zeller, Founder and CEO, Zementis

Whether your company is just beginning to work with predictive analytics or has an experienced data science team, this webinar will provide valuable insights on how to move predictive models into an operational environment based on Hadoop and Hive and using open industry standards while eliminating the custom coding and delays typically associated with these projects.

Register here.


Leave a Reply

Your email address will not be published. Required fields are marked *