Introduction to Machine Learning
This workshop is designed to provide participants with a foundational understanding of the concepts, techniques, and tools used in machine learning. Through a series of lectures and hands-on exercises, participants will learn about types of learning and get practical experience with some of the most popular machine learning algorithms and techniques such as regression, clustering, and neural networks. In addition to learning about the technical aspects of machine learning, this workshop also aims to promote critical thinking about the ethical implications of machine learning. Participants will examine the potential impact of machine learning on society and explore ethical considerations related to data privacy, bias, and fairness.
By the end of the workshop, participants will have a broad understanding of the concepts and techniques used in machine learning, as well as a nuanced understanding of the ethical considerations that underlie this field. This workshop is suitable for anyone who is interested in learning about machine learning, regardless of their technical background or prior experience.
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 UBC Syzygy (https://ubc.syzygy.ca/) or a Google Colaboratory (https://colab.research.google.com/) account. (You will need a CWL login to access Syzygy.)
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.
Disclosure: This description is partially prepared using ChatGPT (https://openai.com/blog/chatgpt).
This workshop is part of the Core Skills series.
If you have any questions, concerns, or accessibility needs please email firstname.lastname@example.org
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- Thursday, April 13, 2023
- 12:00pm - 2:00pm
- All Faculty Graduate
- Digital Scholarship Research Commons
- Shayan Fahimi