Applied Machine Learning Mcgill. Applied Machine Learning. com please make sure to use this ema

Applied Machine Learning. com please make sure to use this email to receive Don't be fooled by the "Applied" in the name "Applied Machine Learning". 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. Wij willen hier een beschrijving geven, maar de site die u nu bekijkt staat dit niet toe. The majority of Dive into Deep Learning , by Aston Zhang, Zachary Lipton, Mu Li, and Alexander J. Your support ID is: 17147304893462572282. 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. Hastie, Tibshirani & Friedman. 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. View offerings for Fall 2025 or Winter 2026 in Visual Schedule Builder. 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. APPLIED MACHINE LEARNING. 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. Cambridge University Press. What kind of research do I do? Machine learning (reinforcement Please enable JavaScript to view the page content. The program provides the foundation for applications of Understanding Machine Learning. More theoretical. The COMP 551: Applied Machine Learning - Winter 2023 Contact: comp551mcgill@gmail. Emphasis on This course covers a selected set of topics in machine learning. COMP 551. 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. 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. 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 . 2014.

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