{"id":2278,"date":"2024-03-19T09:59:18","date_gmt":"2024-03-19T12:59:18","guid":{"rendered":"https:\/\/ccdhhn.ca\/?post_type=tribe_events&p=2278"},"modified":"2024-03-19T10:18:42","modified_gmt":"2024-03-19T13:18:42","slug":"introduction-to-machine-learning-classification-and-clustering","status":"publish","type":"tribe_events","link":"https:\/\/ccdhhn.ca\/fr\/workshop\/introduction-to-machine-learning-classification-and-clustering\/","title":{"rendered":"Introduction to Machine Learning: Classification and Clustering"},"content":{"rendered":"\n
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Event Language<\/h3>\n\tEnglish<\/div>\n\n\n
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Format <\/h3>\n\tvirtual\/virtuel<\/div>\n\n\n
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Cat\u00e9gorie d\u2019\u00c9v\u00e8nement:<\/dt>
1-4 hour workshop<\/a><\/dd><\/div>\n\n\n\n

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.<\/p>\n\n\n\n

In this workshop, we will use cloud-based platforms, so you don\u2019t need to have Python installed. Please make sure that you have a Google Colaboratory (https:\/\/colab.research.google.com\/<\/a>) 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.<\/p>\n\n\n\n

Sign up for other Machine Learning workshops in this series:<\/strong><\/p>\n\n\n\n