{"product_id":"elements-of-machine-learning-9781558603011","title":"Elements of Machine Learning","description":"\u003cp\u003eRecent years have seen an explosion of work on machine learning  the computational study of algorithms that improve performance based on experience. Research on rule induction  neural networks  genetic algorithms  case-based reasoning  and probabilistic inference has produced a variety of robust methods for inducing knowledge from training data. This book covers the main induction algorithms explored in the literature and presents them within a coherent theoretical framework that moves beyond traditional paradigm boundaries.  Elements of Machine Learning provides a comprehensive introduction to the fundamental concepts and problems in the field. The book illustrates a variety of basic algorithms for inducing simple concepts from experience  presents alternatives for organizing learned concepts into large-scale structures  and discusses adaptations of the learning methods to more complex problem-solving tasks. The chapters describe these computational techniques in detail and give examples of their operation  along with exercises and references to the literature.  This text is suitable for use in graduate courses on machine learning. Researchers and students in artificial intelligence  cognitive science  and statistics will find it a useful and informative addition to their libraries.\u003c\/p\u003e","brand":"My Store","offers":[{"title":"Default Title","offer_id":67600414343221,"sku":"ByrdShop_1558603018","price":128.15,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0627\/8139\/0901\/files\/9781558603011.jpg?v=1790970158","url":"https:\/\/atxbooks.com\/products\/elements-of-machine-learning-9781558603011","provider":"ATX Books","version":"1.0","type":"link"}