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analytics and implementation of algorithms in care settings along with clinical, business and ethical challenges will be explored. In addition, an overview of the issues within the health industry
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: Course number and title: MIE1624F/S – Introduction to Data Science and Analytics Course description: The objective of the course is to learn analytical models and overview quantitative algorithms
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: Course number and title: MIE1622H – Computational Finance and Risk Management Course description: The objective of the course is to examine the construction of computational algorithms in solving financial
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edge AI for localized knowledge preservation; AI governance and data sovereignty in digital heritage institutions and collections; study and design of recommendation systems and ranking algorithms used
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to inform enrollment projections and planning Developing and maintaining procedures for administration of examinations Coordinating the preparation and distribution of program and/or course material
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Sessional Instructional Assistant - MAT302H5F - Intro to Algebraic Cryptography (emergency posting)1
University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 2 months agocryptography, from Euclid to Zero Knowledge Proofs. Topics include: block ciphers and the Advanced Encryption Standard (AES); algebraic and number-theoretic techniques and algorithms in cryptography, including
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of work per week, plus on call responsibilities to which will be added an equal distribution of billing overages. Support for relocation expenses will be offered. Should you be interested in
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redirecting as appropriate Creating and updating student records Writing routine documents and correspondence Following rules and procedural instructions when receiving, sorting and distributing mail
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program activities Coordinating program schedules with stakeholders Determining logistical details and activities for events and/or programming Taking and distributing meeting minutes Generating standard
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learning models, including their strengths, deficiencies, and strategies for (hyper)parameter optimization. Prior use of Bayesian optimization or other relevant active learning algorithms is preferred