AutoGOAL is a Python library for automatically finding the best way to solve a given task. It has been designed mainly for Automated Machine Learning (aka AutoML) but it can be used in any scenario where you have several possible ways to solve a given task.

Technically speaking, AutoGOAL is a framework for program synthesis, i.e., finding the best program to solve a given problem, provided that the user can describe the space of all possible programs. AutoGOAL provides a set of low-level components to define different spaces and efficiently search in them. In the specific context of machine learning, AutoGOAL also provides high-level components that can be used as a black-box in almost any type of problem and dataset format.

Overall architecture of the AutoGOAL framework:

AutoGOAL architecture

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Professor (Instructor) at @matcom, University of Havana and Ph.D. student jointly at University of Alicante, working in @knowledge-learning & @autogoal.
Student, getting a major in Computer Science at the University of Havana.
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