Projects are the basic building unit of ML Studio. Each project consists of several parts (not all of them necessary):

Project Information

Each project has its name, owner, date of creation and description.


Files can be attached to a project. They can contain Python scripts, source data, testing data etc. These files can be accessed by using functions, such as readXLSFile()readCSVFile() and executePythonScript().


Tables can be used together with charts as temporary output of the project. It can be used during the modelling to see the results.


Charts are another option how to see results of the modelling.


Libraries are ready-made packs of mathematical and statistical components and functions which can be used in the project. By default ML Studio contains these libraries:


Variables are used for parametrization of projects. This enables the project to be more universal. For more information see Parameters in ML Studio.

Prebuilt functions

ML Studio has been used by BellaDati to prebuilt functions for the most frequent IoT tasks as predictive maintenance and situational intelligence as customer segmentation or market basket analytics. These can be used without the programming, only using graphical interface for the specification of parameters. At the same time it allows partners and organizations to build their own statistical and ML cases.

All of the following functions are supported and solutions can be built:

Deleting Project

A project can be deleted by clicking on the Delete project button under Project information. Please note that this process is IRREVERSIBLE.