Linear algebra review Linear algebra review Daniel Hsu (COMS 4771) Euclidean spaces For each natural number n, the n-dimensional Euclidean space is denoted by Rn, and it is a vector space over the real field R (i.e., Rn is a real vector space). Vectors v1, . . . , vk ∈ Rn are linearly dependent […]
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CS 520 Fall 2021: Final Project CS 520 Final project description Final projects will be completed in teams of 5 students. Each team is responsible for a single project. You should select a team and a project by Tuesday, October 5, 2021, 9:00PM. Your mid-point presentation will be due Tuesday, November 2, 2021, 9:00AM. The
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EECS4404/5327, Winter 2021 Assignment 3 For both parts, you will need to produce a report which you will submit online through eClass. Both parts are due Monday, December 6 at 11:59pm. Late submissions will not be accepted. Mixture Models Consider the Gaussian Mixture Model which assumes the data has been generated from the distribution p(y|θ)
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Topic 5: Principal component analysis 5.1 Covariance matrices Suppose we are interested in a population whose members are represented by vectors in Rd. We model the population as a probability distribution P over Rd, and let X be a random vector with distribution P. The mean of X is the “center of mass” of P.
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Statistical Programming Contents 1 Software Requirements: R, git, JAGS etc 3 1.1 Using a terminal window, choose a text editor . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2 git and github 5 2.1
Writing proofs Tim Hsu, San José State University Revised February 2016 Contents I Fundamentals 5 1 Definitions and theorems 5 2 What is a proof? 5 3 A word about definitions 6 II The structure of proofs 8 4 Assumptions and conclusions 8 5 The if-then method 8 6 Sets, elements, and the if-then method
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Review of Probability Theory Arian Maleki and Tom Do Stanford University Probability theory is the study of uncertainty. Through this class, we will be relying on concepts from probability theory for deriving machine learning algorithms. These notes attempt to cover the basics of probability theory at a level appropriate for CS 229. The mathematical theory
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Natural Language Processing Jacob Eisenstein October 15, 2018 Contents Contents 1 Preface i Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i How to use
KE1068 May 31, 2018 ©2018 by the Kellogg School of Management at Northwestern University. !is case was prepared by Professor Phillip A. Braun. Cases are developed solely as the basis for class discussion. Cases are not intended to serve as endorsements, sources of primary data, or illustrations of e”ective or ine”ective management. Some details may
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Linear Algebra in Twenty Five Lectures Tom Denton and Andrew Waldron March 27, 2012 Edited by Katrina Glaeser, Rohit Thomas & Travis Scrimshaw 1 Contents 1 What is Linear Algebra? 12 2 Gaussian Elimination 19 2.1 Notation for Linear Systems . . . . . . . . . . . . . . .