CSE 255 inthe spring quarter of 2013 was a graduate-level lecture coursedevoted to current methods for data mining and predictiveanalytics. No previous background in machine learning isnecessary, but all participants should be comfortable withprogramming, and following arguments that use calculus and linearalgebra. Although the course will use some mathematics, the focuswill be on useful skills more than on theoretical foundations.
Lecturenotes in the file are updatedevery few days. Please ask questions on.The course meets once a week on Tuesday evenings for ten weeks.Meetings will be from 6:30pm to 9pm in room 2111 of Warren LectureHall (near the CSE building) beginning on Tuesday April 2. Thelast lecture will be on Tuesday June 4. The final exam will be onTuesday June 11 at 7pm.Note that CSE255 used to be numbered CSE 291. To register for thecourse, use section id 779310.datetopicslecture noteshandoutsquizassignmentApril 2Course outline, supervisedlearning, overfittingChapters 1, 2Sample on page 11p. 22April 9Linear regression, preprocessing, missingdata, regularizationChapters 3, 6with solutionp.
29April 16Linear and nonlinear supportvector machinesChapter 5with solutionp. 48April 23Learning when one class is rare, F1 and AUCscoresChapter 7with solutionp. 65April 30Estimating calibrated probabilities, makingcost-sensitive decisionsChapters 8, 9with solutionp.
UCSD DSE MAS. DSE230/CSE255: Data Analysis using Spark. BreakDown Problems, CSE255. The Goal of Breakdown Problems. I learned the idea of breakdown problems from Pavel Pevzner. The basic idea, is that learning is not a linear process: you are given new information, you digest it, and then you move to the next piece of information. Courses.ucsd.edu - Courses.ucsd.edu is a listing of class websites, lecture notes, library book reserves, and much, much more. These course materials will complement your daily lectures by enhancing your learning and understanding. Our prescription? Take two and run to class in the morning.
87May 7Sample selection bias, importance weighting,reject inferenceChapter 10with solutionp. 99May 14Recommender systems, collaborative filtering,matrix factorization via alternating least squaresChapter 11with solutionp.
111May 21Text mining: bag of words representation,classifier learningChapter 12with solutionp. 125May 28Network analytics, link prediction, singularvalue decomposition (SVD)Chapter 14 and Section 13.1with solutionp. 145June 4Guest lecture bywith solutionJune 11For the 2012version of the course, see.
Welcome to!This is a forum where the students, faculty, staff, alumni, and others associated with the University of California San Diego can discuss, share, collaborate, and advise. Rules:.Be nice.Be respectful to others at all times. I did some research on 'data science' classes at UCSD about a year ago, and this is what I found. I wrote this last April, so there is undoubtedly some missing information:Here are some data science related classes currently offered:COGS 9, 14AB, 109, 118AB, 185, 188, 243.