T02 - Machine Learning with Spark

Track: General Track

Session Number: 5001
Date: Mon, May 1st, 2017
Time: 12:45 PM - 1:45 PM
Room: North Exhibit Hall I&J

Description:

Apache Spark defines itself as a fast and general engine for large-scale data processing and it is becoming very popular since its inception. One of the key features of Spark is that it comes with a set of built-in libraries. One of these is MLlib, which is the Spark's Machine Learning library. Machine Learning is a well established field of the data science that studies the algorithms for learning and predicting on data. MLlib brings these algorithms to Spark.<br /><br />In this presentation we will do a short overview of Spark and Machine Learning, and will show how you can benefit from these two worlds.
Session Type: Podium Presentation

Session Code: 4055
Speaker Bio: Emil Kotrc is a principal software engineer at CA Technologies working in the Prague Technology Center since 2005. He started on Resource management products for Mainframe and later moved into Database management for DB2 for z/OS development. Before joining CA Technologies, Emil worked in an academic environment. Emil is an IBM Champion for 2015 and 2016.
Audience experience level: Intermediate
Presentation Category: Emerging Technology
Presentation Platform: Cross Platform
Audiences this presentation will apply to: Application Developers
Technical areas this presentation will apply to: Select a Value
Objective 1: A brief introduction to Spark and integration points.
Objective 2: A brief introduction to Machine Learning - supervised learning vs unsupervised learning.
Objective 3: Basic Machine Learning algorithms - classification and regression algorithms.
Objective 4: Overview of Machine Learning algorithms in MLlib with simple examples.
Session Type: Podium Presentation

Session Code: 4055
Speaker Bio: Emil Kotrc is a principal software engineer at CA Technologies working in the Prague Technology Center since 2005. He started on Resource management products for Mainframe and later moved into Database management for DB2 for z/OS development. Before joining CA Technologies, Emil worked in an academic environment. Emil is an IBM Champion for 2015 and 2016.
Audience experience level: Intermediate
Presentation Category: Emerging Technology
Presentation Platform: Cross Platform
Audiences this presentation will apply to: Application Developers
Technical areas this presentation will apply to: Select a Value
Objective 1: A brief introduction to Spark and integration points.
Objective 2: A brief introduction to Machine Learning - supervised learning vs unsupervised learning.
Objective 3: Basic Machine Learning algorithms - classification and regression algorithms.
Objective 4: Overview of Machine Learning algorithms in MLlib with simple examples.