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Submit talks on data engineering, data science, machine learning, big data and analytics through the year – 2018

Machine Learning with Elasticsearch

Submitted by Aravind Putrevu (@aravindputrevu) on Wednesday, 11 April 2018

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Technical level

Intermediate

Status

Submitted

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Total votes:  +1

Abstract

As volumes of data increase, manually searching and visualising consumer or user behaviours becomes more and more difficult. An alternative approach is to use machine learning to automatically build behavioural models of these behaviours.

These models enable users to gain deep insights into behavioural characteristics that are beyond the capabilities of classical search techniques. Typical use cases include, automatically understanding users that are behaving unusually and understanding the typical behaviour of the population.

This talk will present real examples of machine learning techniques applied to real-time behavioural data, and describe the methodology behind these methods along with an overview of the machine learning space.

Outline

  • Overview of holy grail
  • ML Leaps
  • What is in store from Elastic?
  • What it can/can’t do?
  • Demo

Speaker bio

Aravind is a loquacious person, who has something to talk about everything. He is passionate about evangelising technology, meeting developers and helping in solving their problems. He is a backend developer and has six years of backend development experience.

Previously, He worked at McAfee Antivirus as a Sr. Software Engineer in Cloud Security Domain. He has deep interest in Search, Machine Learning, Security Incident Analysis and IoT tech. In his free time, he plays around Raspi or a Arduino.

Slides

https://speakerdeck.com/aravindputrevu/machine-learning-with-elastic-stack

Preview video

https://youtu.be/2avsR0MWpJI

Comments

  • 1
    Zainab Bawa (@zainabbawa) Reviewer 7 months ago

    Aravind, submit a preview video to complete evaluation for this talk.

  • 1
    Aravind Putrevu (@aravindputrevu) Proposer 7 months ago

    I’ve added a preview video, please check.

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