Enjoy easier scaling, higher elasticity and faster compute on certain algorithms by leveraging Apache Spark™ to fit ML models on large data sets intuitively and easily. Access the TensorFlow™ library through the Splunk MLTK Container for TensorFlow™.

Easily identify changes in website visits and tag odd transactions. Spot the spikes and events that contain unusual value combinations. Discover values that differ significantly from previous ones and find events that contain unusual value combinations.

Make models that fit historical data and predict future numeric values, improving your organization's planning with accurate forecasts. Zero in on just how much to spend on hardware upgrades to support demand, how much to open cell tower bandwidth to accommodate local population growth, etc.

Partition your data with clustering algorithms to figure out which hosts behave similarly or to identify hidden patterns, such as undiscovered trends in online purchases, anomalies in security environments and spikes in resource use.

Build predictive models around numeric or categorical events (numeric or categorical) that are crucial to your business. Use those predictive models for planning, or to uncover anomalies in your earnings, costs, demands, usage, capacity, etc.

Use machine learning SPL (Search Processing Language)
commands to directly build, test and operationalize supervised and unsupervised models. Access the TensorFlow™ library through the Splunk MLTK Container for TensorFlow™, available through certified Splunk Professional Services. Use any of the pre-packaged Python algorithms, or import any of 300+ open-source ones.