Synchronous online recitation times: TBD. Name: Arye Nehorai Email: nehorai ese. Name: Uri Goldsztejn Email: uri. First homework set is designed to assess if students have sufficient background to take this course. Five next sets are assigned biweekly on Tuesdays, and due within two weeks.
E1 244: Detection and Estimation Theory: Homeworks
EE Estimation Theory
This course is focused on statistical learning, estimation, decision theory. Topics include detection theory, likelihood ratio tests, Neyman-Pearson detectors, multiple hypothesis testing, generalized likelihood ratio testing, maximum likelihood estimation, Bayesian inference, empirical risk minimization, concentration inequalities, PAC learning, nonparametric inference. The material is intended for people who have a technical background in engineering, computer science, or mathematics. Students should have knowledge of basic linear algebra, probability, and statistics, as well as some programming experience MATLAB or Python experience is helpful. Students are strongly encouraged to work together on homework assignments, but each student must submit his or her own writeup. Plagiarism of material written by classmates, book or article authors, or web posters is prohibited. Students must work independently on exams.
Anomaly Detection in Scikit-Learn
Reading assignment: Chapter 3 in Kay, vol 2. Display the decision regions in each case and explain. We observe the i. Questions Courses.
Since we are interested in a single score to compare the candidates, instead of measuring the heart rate and the respiration rate, we measure the score of the first principal component PCA of these measurements. Normalize the eigenvector so that it has unit norm. Find the posterior p. Solution: Because the measurements are i. Avoid resits and achieve higher grades with the best study guides, textbook notes, and class notes written by your fellow students.