Mathematics for Machine Learning
Mathematics for Machine Learning

Author: Marc Peter Deisenroth

Publisher: Cambridge University Press

Published: 2020-04-23

Total Pages: 392

ISBN-13: 1108569323

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The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.

Learning by Doing
Learning by Doing

Author: Richard DuFour

Publisher: Solution Tree

Published: 2020

Total Pages: 267

ISBN-13: 9781949539479

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In the third edition of Learning by Doing: A Handbook for Professional Learning Communities at Work®, authors Richard DuFour, Rebecca DuFour, Robert Eaker, Thomas W. Many, and Mike Mattos provide educators with a comprehensive, bestselling guide to transforming their schools into professional learning communities (PLCs). In this revised version, contributor and Canadian educator Karen Power has adapted the third edition for Canadian educators, emphasizing how Canadian educators can effectively improve learning for each student across their unique and widely diverse provinces and territories. Rewritten so that the scenarios, research, and language appropriately meet the needs of Canadian educators, this version is packed with real-world strategies and advice that will assist readers in transforming their school or district into a successful PLC.