Philipp Drieger
Leveraging Graph Neural Networks for Enhanced Security and Observability with Splunk
Discover how Graph Neural Networks (GNNs) enhance security and observability within Splunk. Learn to detect anomalies, predict threats, and optimize system performance using GNNs. Explore the power of graph analytics in your Splunk environment.
Supercharge Cybersecurity Investigations with Splunk and Graphistry: A Powerful Combination for Interactive Graph Exploration
In this blog post, we'll dive deeper into how combining Splunk and Graphistry can help you unlock new capabilities for your cybersecurity investigations and gain better resilience for your organization.
Splunk App for Data Science and Deep Learning - What’s New in Version 5.1.1
In this article, we'll dive into what's new in the recently released Splunk App for Data Science and Deep Learning (DSDL) version 5.1.1 available on Splunkbase now.
Introducing the Splunk App for Data Science and Deep Learning 5.0
Exciting news: The Deep Learning Toolkit App for Splunk (DLTK) will be renamed the Splunk App for Data Science and Deep Learning (DSDL). It’s slightly lengthy, but a better-suited name because the app is useful for both deep learning and data science operations.
Forecasting at Scale: How to Process Millions of Time Series using Prophet and DASK
How do you scale out a specific forecasting use case for millions of entities? Splunker Philipp Drieger gives you the low down and shows you how it's done with the help of DASK and Prophet.
Online Learning: a Novel Approach to Applying Machine Learning in Splunk
In this blog, we’ll review how you can organize your machine learning model in a new way: online learning.
