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SUMMARY:Introduction to Machine Learning: Regression Models
DESCRIPTION:This workshop offers an exploration of machine learning models for clustering and classification. With the increasing availability of large datasets\, these models play a crucial role in extracting valuable insights and making informed decisions. In this 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 preprocess data\, select relevant features\, and evaluate model performance. By the conclusion of the workshop\, participants will have a solid foundation in building and deploying machine learning models for clustering and classification tasks. \n\n\n\nIn 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 (https://colab.research.google.com/) 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. \n\n\n\nSign up for other Machine Learning workshops in this series: \n\n\n\n\nIntroduction to Machine Learning: Neural Networks\n\n\n\n\nOr view other upcoming Digital Scholarship workshops. If participants attend all of “Special Topics in Digital Scholarship” series\, it counts as six hours towards the cc:DH/HN certificate. \n\n\n\nDate: Tuesday\, March 19\, 2024\, 1:00pm – 3:00pm Pacific Time \n\n\n\nPresenter: Vedant Bahel
URL:https://ccdhhn.ca/workshop/2272/
LOCATION:Québec
CATEGORIES:1-4 hour workshop
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