Automated Machine Learning

Machine learning is a branch of computer science that aims at "enabling computers to learn new behavior based on empirical data" (Tantawi, 2016) without being programmed by humans. Algorithms are designed to allow the computer to learn from past experience and use that to display new behavior.

Cognitive computing uses machine learning algorithms to analyze large amounts of data and produce results. Internet searches use cognitive computing to analyze the user's past search behaviors, combined with the current search request, to return results that, based on personal data and the application of patterns, are relevant and useful to the user.

Machine learning, artificial intelligence, and cognitive computing are key players in learning analytics and predictive modeling.

Recently, automated machine learning (AutoML) has become a topic of interest. AutoML automates the entire machine learning process. According to the research group on Machine Learning for Automated Algorithm Design, AutoML provides ways to make Machine Learning available “for non-Machine Learning experts, to improve efficiency of Machine Learning and to accelerate research on Machine Learning" (MLAAD, n.d.).

More on Automated Machine Learning

Marvin, R. (2017, July). Google's AI rewrite: Building machine learning into everythingPC Magazine, 122.

McCracken, H. (2017, November). The great AI war of 2018Fast Company, 220, 64–73.

References

Ingersoll, G. (2015). Getting started with open source machine learning. Retrieved from https://opensource.com/business/15/9/getting-started-open-source-machine-learning

Research group on Machine Learning for Automated Algorithm Design (MLLAD). (n.d.). AUTOML.  Retrieved from http://www.ml4aad.org/automl/

Tantawi, R. (2016). Machine learning. Salem Press Encyclopedia.