Repository with general information about MLSToolbox. The aim of MLSToolbox is to provide a set of tools to support the development of Machine Learning Systems (MLS).
You can find all the information you need in our WIKI!.
| Repository | Description |
|---|---|
| mls_toolbox_client | An Angular-based component for displaying the graphical interface and for requesting the services provided by the MLSToolbox tools |
| mls_toolbox_server | A Flask-based component for redirecting the mls_toolbox_client requests to the services provided by the MLSToolbox tools |
| mls_code_generator | A Python component for mainly generating Python code for the ML pipelines defined in the editor |
| mls_code_generator_config | A repository containing several extensible JSON files that define the graphical elements of the graphical editor representing the predefined steps of a ML pipeline |
| mls_lib | A Python library containing object classes, used in the generated code, representing the structure and the main concepts required to instantiate any pipeline, its stages and the tasks that these stages perform |
| mls_pipeline_examples | A repository containing some examples of ML pipelines defined with the MLS Toolbox Code Generator and the code generated by the tool |
| mls_code_assessment | A Python component for assessing the quality of Python ML pipelines manually implemented |
This video shows how to use the MLSToolbox Pipeline Code generator to define a pipeline and generate the code to create the ML model. More details about the example used in this video are available at mls_code_generator Wiki.
Pipeline.Code.Generator.Diabetes_576.mp4
You can find more videos at mls_code_generator Wiki.
You can find the MLSToolbox Contribution Guidelines here.
You can find the MLSToolbox Code of Conduct here
