Applied Machine Learning Mcgill. com please make sure to use this email to receive Don't be foole

com please make sure to use this email to receive Don't be fooled by the "Applied" in the name "Applied Machine Learning". 2014. View offerings for Fall 2025 or Winter 2026 in Visual Schedule Builder. More theoretical. APPLIED MACHINE LEARNING. Selected topics in machine learning and data mining, including clustering, neural networks, support vector machines, Methods include feature selection and dimensionality reduction, error estimation and empirical validation, algorithm design and parallelization, and handling of large data sets. Credits: 4 O ered by: Computer Science (Faculty of Science) Terms o ered: Fall 2025, Winter 2026 View o erings for Fall 2025 or Winter 2026 in Probabilistic Machine Learning: An Introduction (2022) by Kevin Murphy (Murphy22) Machine Learning: a probabilsitic perspective (2016) by Kevin Murphy (Murphy16) Pattern As an introduction to practical machine learning, these are implementations (from scratch) of logistic regression with gradient COMP 551. COMP 551. The majority of Dive into Deep Learning , by Aston Zhang, Zachary Lipton, Mu Li, and Alexander J. Have already completed the McGill School of Continuing Studies Professional Development Certificate in Data Science and Machine Learning and are seeking to take your machine Areas of application and research enabled by this minor include, among many others, machine learning, computer vision and image generation, natural language processing, data-driven The Master of Engineering in Electrical Engineering; Non-Thesis - Applied Artificial Intelligence is a professional program of 45 credits. The program provides the foundation for applications of Understanding Machine Learning. Cambridge University Press. The majority of sections are related to commonly used supervised learning techniques, and to a lesser degree This course covers a selected set of topics in machine learning and data mining, with an emphasis on good methods and practices for deployment of real systems. Hastie, Tibshirani & Friedman. In COMP 551 we will go very deep into the math and theory of ML while also doing extremely hard, demanding, and This course covers a selected set of topics in machine learning and data mining, with an emphasis on good methods and practices for deployment of real systems. The Elements of Statistical Learning: Data Mining, Inference, and The course will cover selected topics and new developments in data mining and applied machine learning, with a particular emphasis on good methods and practices for e ective deployment of The course will cover selected topics and new developments in data mining and applied machine learning, with a particular emphasis on good methods and practices for e ective deployment of If you are seeking data science knowledge to apply to your profession or to transition into a new career, the Professional Development Certificate in Data Science and Machine Learning gives . Applied Machine Learning. Your support ID is: 17147304893462572282. Emphasis on This course covers a selected set of topics in machine learning. What kind of research do I do? Machine learning (reinforcement Please enable JavaScript to view the page content. Wij willen hier een beschrijving geven, maar de site die u nu bekijkt staat dit niet toe. The COMP 551: Applied Machine Learning - Winter 2023 Contact: comp551mcgill@gmail. Credits:4 Offered by:Computer Science (Faculty of Science) Terms offered:Fall 2025, Winter 2026 Applied Machine Learning (COMP-551) An introduction course on Machine Learning at McGill Univeristy taken during Winter 2021. Smola (2019) Mathematics for Machine Learning , by Marc Peter Deisenroth, A Aldo Faisal, and Cheng Understanding Machine Learning: From Theory to Algorithms, by Shai Shalev-Shwartz and Shai Ben-David (2014) Foundations of Machine Learning, by Mehryar Mohri, Afshin Rostamizadeh, Assistant / Associate Prof at McGill 1993 - 1998 1998 – 2003 2004 - Co-director of the Reasoning and Learning Lab.

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