Common Pitfalls for Applying Machine Learning Models

A distinctive institutionWith a history dating back to 1821, Heriot-Watt University has established a reputation for world-class teaching and practical, leading-edge research, which has made us one of the top UK universities for business and industry.We're a vibrant, forward-looking university, well known for the quality of our degrees with employers actively seeking out our graduates.Heriot-Watt is also Scotland's most international university with an unsurpassed international in-country presence. We deliver degree programmes to 31,000 students globally, have campuses in Dubai and Malaysia and boast the largest international student cohort in Scotland.

Heriot-Watt University Dubai Campus

Heriot-Watt University Dubai

The talk gives a concise outline of some of the common mistakes that occur when using machine learning techniques, and what can be done to avoid them. It is intended primarily as a guide for research students and industry practitioners , and focuses on issues that are of particular concern to validate machine learning models, such as the need to do rigorous comparisons and reach valid conclusions. It covers five stages of the machine learning process: what to do before model building, how to reliably build models, how to robustly evaluate models, how to compare models fairly, and how to report results. It will be held both in person and online via ZoomSpeaker bio : Michael Lones is an Associate Professor of Computer Science at Heriot-Watt University inEdinburgh, Scotland. He received his PhD from the University of York in 2003, and has spentthe last 20 years or so working in the areas of machine learning and data science, authoringaround 80 publications. His early research focused on evolutionary algorithms andbiomedicine, but his interests have since broadened to include other methodological andapplication areas, including neural networks, complex systems, robotics, and computersecurity. He is on the editorial boards for the journals BioSystems and Genetic Programmingand Evolvable Machines, and is a Senior Member of the IEEE and a member of the IEEETechnical Committee on Bioinformatics and Bioengineering.

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Common Pitfalls for Applying Machine Learning Models

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Common Pitfalls for Applying Machine Learning Models

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