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Introduction to large-scale Machine Learning with Apache Flink

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Introduction to large-scale Machine Learning with Apache Flink

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We are having cross meetup event with Big Data Applications meetup to bring another exciting presentation and discussion about Apache Flink.

REGISTRATION

To make sure we have the right head count please visit Big Data Applications meetup page to signup for this talk:

https://www.meetup.com/BigDataApps/events/230880075/

ABSTRACT

Introduction to large-scale Machine Learning with Apache Flink, by Theodore Vasiloudis, SICS

Apache Flink is an open source platform for distributed stream and batch data processing. In this talk we will show how Flink's streaming engine and support for native iterations make it an excellent candidate for the development of large scale machine learning algorithms.

This talk will focus on FlinkML, a new effort to bring scalable machine learning tools to the Flink community. We will provide an introduction to the library, illustrate how we employ some state-of-the-art algorithms to make FlinkML truly scalable, and provide a view into the challenges and decisions one has to make when designing a robust and scalable machine learning library.

Finally, if time permits, we will demonstrate how one can perform some interactive analysis using FlinkML and the notebook environment of Apache Zeppelin.

SPEAKER BIOS

• Theodore Vasiloudis is a Machine Learning researcher, currently performing an internship at Pandora Media. He lives and works in Stockholm at the Swedish Institute of Computer Science (SICS) and is a PhD Candidate at KTH Royal Institute of Technology. His main research interests include large-scale machine learning, graph processing and natural language processing. He is also a contributor to the machine learning library for Apache Flink, FlinkML

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