A comprehensive guide to machine learning
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A comprehensive guide to machine learning
A Comprehensive Guide to Machine LearningSoroush Nasiriany, Garret t Thomas, William Wang, Alex YangDepartment of Electrical Engineering and Computer A comprehensive guide to machine learning Sciences University of California. BerkeleyAugust 13. 20182Aboutcs 189 is the Machine Learning course at L'C Berkeley. In this guide we have created a comprehensive course guide in order to share our knowledge with students and the general public, and hopefully draw the interest of students from ot A comprehensive guide to machine learning her universities to Berkeley’s Machine Learning curriculum.This guide was started by cs 189 TAs Soroush Nasiriany and Garrett Thomas in Fall 2017, wiA comprehensive guide to machine learning
th t he assistance of William Wang and Alex Yang.We owe gratitude to Professors Anant Sahai, Stella Yu, and Jennifer Listgartcn, as this book is heaviA Comprehensive Guide to Machine LearningSoroush Nasiriany, Garret t Thomas, William Wang, Alex YangDepartment of Electrical Engineering and Computer A comprehensive guide to machine learning at ion.The latest version of this document can be found either at http://www.eecsl89.org/ or http: //snasiriany.me/csl89/. Please report any mistakes to the staff, and contact the authors if you wish to redistribute this document.NotationNotationMeaningR R” pmxn v/(x) V‘/(x) pW p(x) E[X) Var(A) Cov( A comprehensive guide to machine learning A,Y)set of real numbers set (vector space) of n-tuples of real numbers, endowed wit h the usual inner product set (vector space) of m-by-n matrices KrA comprehensive guide to machine learning
onedeer della, i.e. &,j = 1 if i = j. 0 otherwise gradient of the function f at X Hessian of the function f at X distribution of random variable A' prA Comprehensive Guide to Machine LearningSoroush Nasiriany, Garret t Thomas, William Wang, Alex YangDepartment of Electrical Engineering and Computer A comprehensive guide to machine learning YOther notes:•Vectors and matrices are in bold (c.g. X. A). This is true for vectors in Rn as well as for vectors in general vector spaces. We generally use Greek letters for scalars and capital Boman letters for matrices and random variables.•We assume that vectors arc column vectors, i.c. that, a A comprehensive guide to machine learning vector in Rn can be interpreted as an n-by-1 mat rix. As such, taking t he transpose of a vector is well-defined (and produces a rowvector, which isA comprehensive guide to machine learning
a 1-by-n mat rix).Contents1Regression I51.1Ordinary Least Squares..................................................... 51.2Ridge Regression...........A Comprehensive Guide to Machine LearningSoroush Nasiriany, Garret t Thomas, William Wang, Alex YangDepartment of Electrical Engineering and Computer A comprehensive guide to machine learning and Validat ion.......................................... 122Regression II172.1MLE and MAP for Regression (Part I)....................................... 172.2Bias-Variance Tradeoff................................................... 232.3Multivariate Gausshms......................................... A comprehensive guide to machine learning ........... 302.4MLEA comprehensive guide to machine learning
................... 442.6Sjmrsc Least. Squares.................................................... 502.7Total Least Squares ..........................A Comprehensive Guide to Machine LearningSoroush Nasiriany, Garret t Thomas, William Wang, Alex YangDepartment of Electrical Engineering and Computer A comprehensive guide to machine learning Correlation .Analysis.......................................... 704Beyond Least Squares:Optimization and Neural Networks794.1Nonlinear Least Squares................................................... 794.2Optimization............................................................. 81 A comprehensive guide to machine learning A Comprehensive Guide to Machine LearningSoroush Nasiriany, Garret t Thomas, William Wang, Alex YangDepartment of Electrical Engineering and ComputerGọi ngay
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