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Philipp
Philipp Drieger

Philipp Drieger works as a Principal Machine Learning Architect at Splunk. He accompanies Splunk customers and partners across various industries in their digital journeys, helping to achieve advanced analytics use cases in cybersecurity, IT operations, IoT and business analytics. Before joining Splunk, Philipp worked as freelance software developer and consultant focussing on high performance 3D graphics and visual computing technologies. In research, he has published papers on text mining and semantic network analysis.

Platform 2 Min Read

Deep Learning Toolkit 3.3 - Examples for Explainable AI and XGBoost

Discover the latest version of the Deep Learning Toolkit App for Splunk (DLTK) 3.3 and take a look at a recent addition to the family of algorithms in DLTK: XGBoost.
DevOps 3 Min Read

MLOps - Logs, Metrics and Traces to improve your Machine Learning Systems

Deployment of machine learning models to production needs monitoring of operations and performance. This is where Machine Learning Operations (MLOps) comes into play. Find out what it is and how it works in this article.
Platform 4 Min Read

The Words of the Birds - Leveraging AI to Detect Songbirds

What if you had an AI system that could identify the birds around you based on their sounds? Well, Splunker Philipp Drieger did and shares his findings in this article.
Platform 3 Min Read

Deep Learning Toolkit 3.1 - Examples for Prophet, Graphs, GPUs and DASK

This blog post highlights our customer's data scientists most demanded use cases and new algorithms for our recently released Splunk Deep Learning Toolkit 3.1.
Platform 2 Min Read

Deep Learning Toolkit 3.1 - Release for Kubernetes and OpenShift

With the launch of Splunk’s Machine Learning Toolkit 5.2, we have also released a new Deep Learning Toolkit for Splunk (DLTK) along with a brand new “golden” container image. Read all about it here.