HIGH-PERFORMANCE INTERACTIVE SQL ANALYTICS AND MACHINE LEARNING ON HADOOP

Pivotal

Already strategic partners, Pivotal Software and Hortonworks deepened their relationship in Spring 2016 with the goal of providing enterprises the most complete modern data platform for advanced analytics and machine learning. As part of the expanded relationship, Hortonworks has introduced Hortonworks HDB, the market’s leading Hadoop Native SQL database and big data SQL machine learning engine based on Apache HAWQ and Apache MADlib (incubating).
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Spotlight

The Data, Analytics and Institutional Research team collaborated with partners from across the campus. They conducted stakeholder analysis, engaged subject matter experts, and held forums with vendors and academic partners. The end result was the launch of the Insights Program, a comprehensive approach to data warehousing and predictive analytics.


OTHER ON-DEMAND WEBINARS

A Tour of Enthought’s Latest Enterprise Python Solutions

Canopy

What: A comprehensive overview and live demonstration of Enthought’s latest tools for Python for the enterprise with Enthought’s Chief Technical & Engineering Officer, Didrik Pinte. Who Should Attend: Python users (or those supporting Python users) who are looking for a universal solution set that is reliable and “just works”; scientists, engineers, and data science teams trying to answer the question “how can I more easily build and deploy my applications”; organizations looking for an alternative to MATLAB that is cost-effective, robust, and powerful.
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Descriptive, Prescriptive, and Predictive Analytics

DATAVERSITY

Data analysis can be divided into descriptive, prescriptive and predictive analytics. Descriptive analytics aims to help uncover valuable insight from the data being analyzed. Prescriptive analytics suggests conclusions or actions that may be taken based on the analysis. Predictive analytics focuses on the application of statistical models to help forecast the behavior of people and markets.
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A NEW ERA OF DATA SCIENCE: Unlocking Big Data Insights with Machine Learning and Spark

SmarterHQ

join Dean Abbott, internationally recognized data mining and predictive analytics expert and Dr. Mamdouh Refaat, Senior Vice President and Chief Data Scientist at Angoss, for a discussion on:Big Data technologies and trends.Importance of Data Science: Predictive Analytics, Machine Learning, AI, and BI.
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A Data Scientist’s Guide to Modeling Engine Degradation

Data Science Central LLC

With the growth of connected “things”, industries are presented with huge opportunities to leverage sensor data to improve their operations, products and services. With the proliferation of these devices, competitive advantages will develop from appropriate leveraging of the deluge of data. From connected appliances to jet engines, industries are already undergoing massive transformations. Critical to success is the ability to not only collect data from sensors, but to also leverage big data technologies and data science expertise to extract actionable insights from the data.
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Spotlight

The Data, Analytics and Institutional Research team collaborated with partners from across the campus. They conducted stakeholder analysis, engaged subject matter experts, and held forums with vendors and academic partners. The end result was the launch of the Insights Program, a comprehensive approach to data warehousing and predictive analytics.

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