Consider that Splunk offers a three-tier architecture for machine learning defined as:
- Tier 1: Core platform searching features
- Tier 2: Packaged solutions and apps offered on Splunkbase
- Tier 3: Using the Splunk Machine Learning Toolkit
Since tier 1 and tier 2 should be self-explanatory to you at this point, let's have a closer look at tier 3.
To define the Machine Learning Toolkit, we will start with a typical machine learning project so as to understand what type of work will be carried out by most data scientists. These work efforts are:
- Collect (data)
- Clean and transform (data)
- Explore and visualize (data)
- Model (data)
- Evaluate (the results of the model)
- Deployment (once the predictions are made, how can they be put to use?)
