{"product_id":"machine-learning-an-algorithmic-perspective-second-edition-9781466583283","title":"Machine Learning: An Algorithmic Perspective, Second Edition","description":"\u003cp\u003e • Author(s): Stephen Marsland\u003cbr\u003e • Publisher: CRC Press\u003cbr\u003e • Publisher Imprint: CRC Press\u003cbr\u003e • BISAC: Data Science - Data Analytics\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cem\u003eA Proven, Hands-On Approach for Students without a Strong Statistical Foundation\u003c\/em\u003e\u003c\/p\u003e\u003cp\u003eSince the best-selling first edition was published, there have been several prominent developments in the field of machine learning, including the increasing work on the statistical interpretations of machine learning algorithms. Unfortunately, computer science students without a strong statistical background often find it hard to get started in this area. \u003c\/p\u003e\u003cp\u003eRemedying this deficiency, \u003cstrong\u003eMachine Learning: An Algorithmic Perspective, Second Edition\u003c\/strong\u003e helps students understand the algorithms of machine learning. It puts them on a path toward mastering the relevant mathematics and statistics as well as the necessary programming and experimentation.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eNew to the Second Edition\u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e \u003cli\u003eTwo new chapters on deep belief networks and Gaussian processes \u003c\/li\u003e \u003cli\u003eReorganization of the chapters to make a more natural flow of content\u003c\/li\u003e \u003cli\u003eRevision of the support vector machine material, including a simple implementation for experiments\u003c\/li\u003e \u003cli\u003eNew material on random forests, the perceptron convergence theorem, accuracy methods, and conjugate gradient optimization for the multi-layer perceptron\u003c\/li\u003e \u003cli\u003eAdditional discussions of the Kalman and particle filters\u003c\/li\u003e \u003cli\u003eImproved code, including better use of naming conventions in Python\u003c\/li\u003e \u003c\/ul\u003e\u003cp\u003eSuitable for both an introductory one-semester course and more advanced courses, the text strongly encourages students to practice with the code. Each chapter includes detailed examples along with further reading and problems. All of the code used to create the examples is available on the author's website. \u003c\/p\u003e","brand":"CRC Press","offers":[{"title":"Hardcover","offer_id":45299160744087,"sku":"9781466583283","price":6954.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9781466583283.webp?v=1769285151","url":"https:\/\/atlanticbooks.com\/products\/machine-learning-an-algorithmic-perspective-second-edition-9781466583283","provider":"Atlantic Books","version":"1.0","type":"link"}