31 Jan 2024 Introduction to Machine Learning in Python: classification and clustering
This workshop has already taken place. For more information about the workshop, including schedule, slides, etc go to: https://ubc-library-rc.github.io/ml-classification-clustering/
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This workshop offers an exploration of machine learning models for clustering and classification. Participants will gain insight into clustering algorithms such as K-means, explore popular classification algorithms like decision trees, and learn about anomaly detection. Through a combination of lectures and hands-on exercises, which will help participants learn how to pre-process data, select relevant features, and evaluate model performance, participants will gain a solid foundation in building and deploying machine learning models for clustering and classification tasks.
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TITLE: Introduction to Machine Learning in Python: classification and clustering
WHEN: Wednesday, January 31st, 2024 at 12:00 noon PST [convert to your local time]
WHERE: This is a free online webinar.
SPEAKER: Shayan Fahimi, Ph.D., Research Engineer, Composites Research Network, The University of British Columbia.
About the topic: This 2-hour workshop offers an exploration of machine learning models for clustering and classification. Given the growing availability of large datasets, these models play a crucial role in extracting valuable insights and facilitating well-informed decision making. Throughout the workshop, participants will gain insight into clustering algorithms such as K-means, explore popular classification algorithms like decision trees, and learn about anomaly detection. Through a combination of lectures and hands-on exercises, participants will learn how to pre-process data, select relevant features, and evaluate model performance. By the end of this workshop, participants will have a solid foundation in building and deploying machine learning models for clustering and classification tasks.
In this workshop, we will use cloud-based platforms, so you don’t need to have Python installed. Please make sure that you have a Google Colaboratory account. This workshop will involve hands-on exercises that require the use of programming tools and libraries commonly used in machine learning, such as Python and Scikit-learn. As such, prior familiarity with Python programming is recommended for participants to fully benefit from the practical component of the workshop.
About the speaker: Shayan Fahimi earned his PhD in Structural Engineering from the University of British Columbia. He currently serves as a Lecturer in the Department of Civil and Mechanical Engineering and holds a Research Engineer position at Composite Research Network at UBC. His expertise lies in the numerical analysis of manufacturing processes, highly nonlinear materials, and multiphase systems. In addition to his academic roles, Shayan has conducted workshops on numerical modeling techniques and machine learning methods as a member of the Digital Scholarship team at UBC. Beyond his teaching and research activities, Shayan provides consultation services in computational reproducibility, containerization and cloud-computing, and physics-based machine learning methods. In his free time, Shayan finds enjoyment in Latin dances and hiking.
About the TI Methods Speaker Series: The TI Methods Speaker Series are offered free of charge and everyone is welcome. The event is usually held at noon on the last Wednesday of each month via Zoom videoconference. The presentations are recorded and the video recordings are posted online. Click here to view the list of talks offered in 2024.
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