What Is Meta-Learning in Machine Learning?

Meta-learning in machine learning refers to learning algorithms that learn from other learning algorithms.

Most commonly, this means the use of machine learning algorithms that learn how to best combine the predictions from other machine learning algorithms in the field of ensemble learning.

Nevertheless, meta-learning might also refer to the manual process of model selecting and algorithm tuning performed by a practitioner on a machine learning project that modern automl algorithms seek to automate. It also refers to learning across multiple related predictive modeling tasks, called multi-task learning, where meta-learning algorithms learn how to learn.

In this tutorial, you will discover meta-learning in machine learning.

After completing this tutorial, you will know: