Machine Learning Toolkit Blogs

For centuries there have been many wise sayings on how to deal with disruptions and prevail amidst uncertain circumstances. Read on to learn how Splunk and Bosch Rexroth are building the next-generation factory to help manufacturers elevate their resilience and take advantage of new market trends and operating models.

We’re happy to announce that with the upcoming release of DSDL 5.1.1 we’re significantly overhauling the build process for containers in DSDL.

The Splunk Machine Learning ToolKit (MLTK) now enables users to upload their pre-trained models in MLTK with a simple UI.

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.

Identifying anomalies in data is the top use for machine learning in Splunk. Here we will take you through a simple method for how you can detect anomalies on your data using SPL.

Dive into the concepts and resources to help get familiar with using the Splunk Machine Learning Toolkit, and get a look at some of the new content we’re working on to help you get more insight from your data using machine learning.

How do you organize the data flow in Splunk Enterprise or Splunk Cloud? Splunker Philipp Drieger shares typical data pipeline patterns that will help you improve your existing or future machine learning workflows with MLTK or DLTK.

We’re excited to share that the Deep Learning Toolkit App for Splunk (DLTK) is now available in version 3.6 for Splunk Enterprise and Splunk Cloud. Read all about the updates here.

When your datasets are far from simple, your anomaly detection techniques must evolve to scale with the growing complexity. In this blog, you will learn various ways to take your anomaly detection to the next level no matter the complexity of your data.