Philipp Drieger
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.
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.
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.
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.
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.
