#splunkconf19 Preview: Machine Learning

Hello, Las Vegas! Splunk .conf19 is quickly approaching on October 21-24, and we’re here to help you select the most interesting machine learning sessions to attend based on your experience level and unique interests.

With 50+ sessions around machine learning use cases such as predicting outages, security monitoring, fraud detection, forecasting disk usage, anomaly detection, etc., we have a talk for everyone no matter if you're just starting out or looking for advanced-level machine learning use cases.

Just starting with machine learning? Check out these sessions:

• FN1213 - The Two Most Common Machine Learning Solutions Everyone Needs to Know
  (Wednesday, October 23, 12:30-1:15pm)
  Eurus Kim, Staff ML Architect, Splunk
  Amir Malekpour, Principal Software Engineer, Machine Learning, Splunk

Join Eurus and Amir as they show you the basics of how you can understand your data, get your data ready for machine learning, and get the machine to start working for you! Demystify machine learning and get a practical guide to applying machine learning techniques for numeric outlier detection, and forecasting.

• FN1470 - Machine Learning & Splunk 2019: The Splunk Machine Learning Toolkit in Action
  (Tuesday, October 22, 1:45-2:30pm)
  Iman Makaremi, Principal Product Manager – Machine Learning and AI, Splunk
  Harsh Keswani, Product Manager – Machine Learning, Splunk

Iman and Harsh will reveal the most popular Splunk Machine Learning Toolkit use-cases and will address how the toolkit might be useful for your work.

• FN1553 - The New Experiment Experience in the Splunk Machine Learning Toolkit
  (Wednesday, October 23, 4:15-5pm)
  Gyanendra Rana, Senior Product Manager, Splunk
  Ryan Oriecuia, Principal Software Developer, Splunk

Want to know what’s new in the MLTK Experiment Framework? Join Gyanendra and Ryan to find out how we're changing the experiment workflow to reflect real-world usage of the MLTK and making it easier for people new to the MLTK to get up and running.

Interested in tried and tested use-cases? Find out how Splunk customers and partners are leveraging the Splunk Machine Learning Toolkit:

• IoT1603 - Splunk electrified: Building a modular application for the new Porsche Taycan
  (Wednesday, October 23, 11:15am-12pm)
  Tim Klapper, Service Manager Splunk, Porsche
  Tobias Schug, Senior Software Engineer, Porsche
  
  
• FN1137 - Forecasting Disk Usage with Machine Learning – So easy, even a cave-person can do it!
  (Tuesday, October 22, 1:45-2:30pm)
  Steve Koelpin, Splunk Advisor, TransUnion
  Alicia Dale, Site Reliability Engineer, TransUnion
  
  
• IT1722 - Predict Real-World Outages using Splunk MLTK
  (Wednesday, October 23, 12:30-1:15pm)
  Vijay Veggalam, Member of Technical Staff, T-Mobile
  Gintaras Gaigalas, Sr. RF Engineer, T-Mobile
  
  
• IoT1629 - Deep Dive: How to use Splunk to protect the environment
  (Tuesday, October 22, 3-3:45pm)
  Charlie Studdard, Machine Data Analytics, Honda Manufacturing of Alabama
  
  
• SEC1374 - Augment Your Security Monitoring Use Cases with Splunk's Machine Learning Toolkit
  (Thursday, October 24, 11:45am-12:30pm)
  Oliver Kollenberg, Security Consultant, Siemens AG
  Philipp Drieger, Staff Machine Learning Architect, Splunk

Interested in level-up use cases? Check out these sessions:

• SEC1904 - The Duck Test: Leverage Machine Learning to Remediate Fraud in Huge Datasets
  (Thursday, October 24, 1-1:45pm)
  Matthew Harper, Director, Cyber Crime Prevention, Aflac
  
  
• FN1366 - Enhanced Anomaly Detection: Join T-Mobile and Splunk as we Deep Dive an Enterprise-IT Operational Use Case
  (Wednesday, October 23, 1:45-2:30pm)
  Iman Makaremi, Principal Product Manager – Machine Learning and AI, Splunk
  Scott Garcia, MTS - Member Technical Staff, T-Mobile

Want more?

Check out the full list of machine learning sessions and be sure to add them to your Session Scheduler. 

If you have not yet registered for .conf19, reserve your spot while you can.

Have some questions or use cases to share? Reach out to the Machine Learning Team at the source=*Pavilion.

Visit the Splunk ML team at the Splunk Innovation Labs to learn what we’re working on. (*Splunk Innovation Labs will not be open on Thursday).

Looking forward to seeing you at .conf19. Happy Splunking!

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