The very first thing required when starting a Machine Learning project in Knowi is to create a workspace. A workspace can be thought of as a folder that will contain all your subsequent machine learning models for the particular use case in question.
Once the workspace is created and the required type of modelling determined, the user is then required to either select or upload their training dataset. This dataset will include historical data relating to the predictor variable they wish to predict. The example flow below is for supervised learning (classification and regression). For Anomaly Detection, please click here.
The user is then able to perform Cloud9QL upon the training dataset, select the variable they wish to predict and also analyze their data to not only see the columns present in their training dataset, but they can also view statistical information about the data in each column by clicking on the icon in each column header.
Once the data is uploaded and the attribute to be predicted has been selected, the user then selects Prepare Data. This will then guide the user step by step through some tasks designed to help clean the data items ready for the machine learning algorithms to use.
When entering the Machine Learning module, the user will automatically be taken to a list of their current workspaces and published models. To edit a previously created workspace, simply click on the edit icon next to the workspace name.