4.1. Overview

MLPro provides a subtopic package for supervised learning, namely MLPro-SL. At the moment, the implementation is still limited but we are working on it and improving it to bring you full supervised learning functionalities in the near future. MLPro-SL is designed to handle online and offline supervised learning, which means that the model can be used for different purposes, e.g. model-based reinforcement learning, online adaptivity, and more.

The current implementation covers:

• A base class of an adaptive function for supervised learning

• A base class of an adaptive function for feedforward neural networks, including MLP

• Ready-to-use PyTorch-based MLP networks in the pool of objects

Learn more

• Getting started with MLPro-SL

Cross Reference

• API Reference: MLPro-SL

• API Reference: MLPro-SL Pool of Objects