RMIT Classification: Trusted Introduction COSC 2673-2793 | Semester 1 2021 (Computational) Machine Learning Image: Freepik.com RMIT Classification: Trusted Agenda • Introduction – Teaching Team. • Overview of the course. • Foundations of ML. By the end of the lecture, you will: • Understand what the course is about and the assignment structure. • Have a […]
Quiz 1 Question 1 If 99.9% of your sequential program execution time is spent inside a loop that can be parallelized, what is the maximum speedup you can achieve via parallelizing this loop? 49 Quiz 1 Question 1 If 99.9% of your sequential program execution time is spent inside a loop that can be parallelized,
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CONCURRENCY: DEADLOCK + Review Andrea Arpaci-Dusseau CS 537, Fall 2019 ADMINISTRIVIA Project 5 available now (xv6 Memory) – Topic of Discussion Sections tomorrow – Due Monday 11/4 (5 pm) – Request new project partner if desired (web form) – Turn in any of 3 versions: – v0 (alloc alternating pages, all marked as UNKNOWN PID)
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CS 537 – Introduction to Operating Systems Fall 2019 Instructor: Andrea Arpaci-Dusseau Exam 3 — Final Exam: Persistence Fill in these fields on the scantron form (use #2 pencil): 1. LAST NAME (surname) and FIRST NAME (given name), fill in bubbles 2. IDENTIFICATION NUMBER is your Campus ID number, fill in bubbles 3. Under F
RMIT Classification: Trusted Evaluating Hypotheses & Bayesian Learning COSC 2673-2793 | Semester 1 2021 (computational) Machine Learning Image: Freepik.com RMIT Classification: Trusted Assignment 1 COSC 2673-2793 | Semester 1 2021 (computational) Machine Learning Image: Freepik.com RMIT Classification: Trusted Key Dates and Important Information Ø Assignment Type: Individual Ø Due: Friday 16th April 2021 (Week 6)
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Limits of Computation 2020/21 Part V Complexity: Various Problems and NP(Some notes on Lectures 16–18) Bernhard Reus March 15, 2021 16 Problems in P In this section we will have a closer look at some “natural” problems that we encounter quite often in practice. All of them are quite famous (some more than others). In
Limits of Computation 13 – Complexity Classes Bernhard Reus 1 The complexity story so far • time measure for machine like languages • and for WHILE • discussed fairness • comparing timed programming languages 2 THIS TIME • • • • Time Complexity We deal with worst case time complexity, so we need upper bounds
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T/F Questions: Practice Exam 2 1. (T/F) Problem X is in NP, and if it can be solved in polynomial time, then P=NP. 2. (T/F) If a problem X can be written as an Integer Linear Program, and X can be solved in polynomial time, then P = NP. 3. (T/F) X is the problem
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PERSISTENCE: I/O DEVICES Andrea Arpaci-Dusseau CS 537, Fall 2019 ADMINISTRIVIA Grades: Project 3 (email TAs if problems) Project 5 available now (xv6 Memory) – Due Monday 11/4 (5 pm) – Many lab hours through then – Turn in any of 3 versions: – v1a (alloc alternating pages, all marked as UNKNOWN PID) – v1b (alternating
RMIT Classification: Trusted Regularisation COSC 2673-2793 | Semester 1 2021 (Computational) Machine Learning COSC2673 | COSC2793 Week 3: Regularisation 1 Image: Freepik.com RMIT Classification: Trusted Regression Assumptions/Issues Temperature Temperature Temperature 𝜃! +𝜃”𝑥” 𝜃! +𝜃”𝑥” +𝜃#𝑥”# 𝜃! +𝜃”𝑥” +𝜃#𝑥”# +𝜃$𝑥”$ +𝜃%𝑥”% … COSC2673 | COSC2793 Week 3: Regularisation 2 Power consumption Power consumption Power consumption RMIT
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