Cloud customers can use GitHub algorithms via this app and need to create a support ticket to have this installed: The GitHub repo algorithms are also available as an app which provides access to custom algorithms. Splunk Community for MLTK Algorithms on GitHubĬheck out our Open Source community on Github that lets you share your algorithms with the community of Splunk MLTK users or import one of the algorithms that have been shared by the community: Python expertise is required to create your own neural networks. It extends Splunk’s Machine Learning Toolkit with prebuilt Docker containers for TensorFlow 2.0, PyTorch and a collection of NLP libraries.
Integrate with advanced custom machine learning systems using the Deep Learning Toolkit for Splunk (). *Smart Forecasting Assistant (provides enhanced time-series analysis for users with little to no SPL knowledge and leverages the StateSpaceForecasting algorithm): e.g. Smart Assistants (new assistants with revamped UI and better ml pipeline/experiment management):
forecast data center growth and capacity planning. detect outliers in diabetes patient records. * Detect Categorical Outliers (probabilistic measures): e.g. * Detect Numeric Outliers (distribution statistics): e.g. * Predict Categorical Fields (Logistic Regression): e.g. * Predict Numeric Fields (Linear Regression): e.g.
Splunk cloud vs splunk enterprise code#
You can inspect the assistant panels and underlying code to see how it all works. The Splunk Machine Learning Toolkit App delivers new SPL commands, custom visualizations, assistants, and examples to explore a variety of ml concepts.Įach assistant includes end-to-end examples with datasets, plus the ability to apply the visualizations and SPL commands to your own data.