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Machine learning (ML) helps companies leverage data to improve intelligence in their operations. In this webinar, we’ll show you how to analyze data with different forms of machine learning using Splunk, comparing stream and batch processing. Splunk Streaming ML gives you the ability to extract near real-time insights from data as it is ingested. These capabilities can be complementary to traditional batch methodology, and so we’ll also demonstrate how the Splunk Machine Learning Toolkit (MLTK) can be leveraged to train models from your data.

Join Lila Fridley, Sr. Product Manager, Splunk ML and Kristal Curtis, Sr. Software Engineer, Splunk Applied Research as they showcase two different demos across the same use case to give you a sense of how you can approach your data needs from different angles:

  • Streaming Machine Learning using Splunk Data Stream Processor (DSP)
  • Batch Machine Learning using the Splunk Machine Learning Toolkit (MLTK)

Join us to get a glimpse into how you can put ML to work for you!