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.

Mathematics and the Divine seem to correspond to diametrically opposed tendencies of the human mind. Does the mathematician not seek what is precisely defined, and do the objects intended by the mystic and the theologian not lie beyond definition? Is mathematics not Man's search for a measure, and isn't the Divine that which is immeasurable ?The present book shows that the domains of mathematics and the Divine, which may seem so radically separated, have throughout history and across cultures, proved to be intimately related. Religious activities such as the building of temples, the telling of ritual stories or the drawing of enigmatic figures all display distinct mathematical features. Major philosophical systems dealing with the Absolute and theological speculations focussing on our knowledge of the Ultimate have been based on or inspired by mathematics. A series of chapters by an international team of experts highlighting key figures, schools and trains of thought is presented here. Chinese number mysticism, the views of Pythagoras and Plato and their followers, Nicholas of Cusa's theological geometry, Spinozism and intuitionism as a philosophy of mathematics are treated side by side among many other themes in an attempt at creating a global view on the relation of mathematics and Man's quest for the Absolute in the course of history.·Mathematics and man's quest for the Absolute·A selective history highlighting key figures, schools and trains of thought ·An international team of historians presenting specific new findings as well as general overviews·Confronting and uniting otherwise compartmentalized information

Drawing a line, and then another, and another. Go back from the lines to the movements they capture and see gestures in them: not spatial displacements, but modes of knowledge that pass through the exercise of the body. Discovering something new in a gesture: the line that contracts into a point or the point that expands into a zone, perhaps sinking into a hole. Thus experiencing a diagram: a becoming other inscribed in the novelty of the gesture and in the changes of the forms it shapes. This and much more is discussed in the essays gathered in Diagrams and Gestures. Resulting from trans-disciplinary work between mathematicians, philosophers, linguists and semioticians, the volume delivers an up-to-date account of the most valuable research on the connections between gesture and diagram. As one of the most important themes in contemporary thought, the study of these connections poses a challenge for the future: to elaborate a theory that is equal to new and stimulating research methodologies. We call this theory a philosophy of diagrammatic gestures.