2/14/20 1 The Relational Data Model 2. The Relational Data Model • use a simple and uniform data structure: the relation • has been implemented in most commercial database systems • has a solid theoretic foundation. 2/14/20 2 2.1 Structures • In the relational model, everything is described using relations. • A relation can be […]
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Advanced Cryptanalysis Linear and Differential Cryptanalysis CS 3IS3 Ryszard Janicki Department of Computing and Software, McMaster University, Hamilton, Ontario, Canada Acknowledgments: Material based on Information Security by Mark Stamp (Chapter 6.4) Ryszard Janicki Linear and Differential Cryptanalysis 1/41 Introduction Both linear and differential cryptanalysis developed to attack DES (Data Encryption Standard) Applicable to other block
Networking Basics CS 3IS3 Ryszard Janicki Department of Computing and Software, McMaster University, Hamilton, Ontario, Canada Acknowledgments: Material based on Information Security by Mark Stamp (Appendix 1) Ryszard Janicki Networking Basics 1/27 Network If you already had Network course, this part is redundant, but I realize many students did not take Network course yet and
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3/30/2021 CSE 473/573 ‘- Introduction to Computer Vision and Image Processing 1 Using K-NN • Simple, a good one to try first • With infinite examples, 1-NN provably has error that is at most twice Bayes optimal error 2 ‘- 1 3/30/2021 Sec. 15.1 Support Vector Machine (SVM) • SVMs maximize the margin around the
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PowerPoint Presentation Machine Learning Lecture: Multi-Layer ANNs C.-C. Hung Slides used in the classroom only Reference Simon Haykin, Neural Networks: A Comprehensive Foundation, IEEE Press, 1994 Lecture overview Recall Perceptron Multi-Layer ANNs Backpropagation Neural Networks (BNN) Training Backpropagation in ANNs Recap: Can a single neuron learn a task? In 1958, Frank Rosenblatt introduced a training
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Final Exam Practice Total m arks m in s 100 120 I. (20) For the average reward setting , the the G) Show value function EG) : Er [?÷fRk- re’t)))SED differential state is defined as : where the reward , average [LEIRen] rich = laing Ee . Derive the following Bellman equation for the ZaRats)3.PG’s-
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Final Exam Practice Total m arks m in s 100 120 I. (20) For the average reward setting , the the G) Show value function EG) : Er [?÷fRk- re’t)))SED differential state is defined as : where the reward , average [LEIRen] rich = laing Ee . Derive the following Bellman equation for the ZaRats)3.PG’s-
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Module 1: Introducing the Training and Understanding ATT&CK ©2019 The MITRE Corporation. ALL RIGHTS RESERVED Approved for public release. Distribution unlimited 19-01075-15. Using MITRE ATT&CKTM for Cyber Threat Intelligence Training Katie Nickels and Adam Pennington ©2019 The MITRE Corporation. ALL RIGHTS RESERVED Approved for public release. Distribution unlimited 19-01075-15. Training Overview ▪ Five modules consisting
Announcements • You should be able to see the correct answers/feedback in your Midterm on CourseLink now • Exemplar answers are now posted under Midterm Prep & Results folder CIS 3760 Software Engineering 1 Some QA Humour…from Steph Beach, QA Geek • https://www.youtube.com/watch?v=o2Qxf07kggM • https://www.youtube.com/watch?v=imrp-xFOx_I CIS 3760 Software Engineering 2 CIS 3760: Software Engineering Software
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Programmes: MSc Computer Science / MSc Information Science (Data Analytics) Module Code: KC7013 Module Title: Database Modelling Distributed on: Thursday 25th March 2021 Submission Time and Date: Wednesday 19th May 2021 by 23.59 GMT Date by which Work and Feedback will be returned to Students: Wednesday 16th June 2021 Weighting This coursework accounts for 50%
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