{"product_id":"9781461375272","title":"Learning to Learn","description":"\u003ch1\u003eLearning to Learn\u003c\/h1\u003e \u003ch2\u003eThrun, Sebastian; Pratt, Lorien\u003c\/h2\u003e \u003cp\u003eOver the past three decades or so, research on machine learning  and data mining has led to a wide variety of algorithms that learn  general functions from experience. As machine learning is maturing, it  has begun to make the successful transition from academic research to  various practical applications. Generic techniques such as decision  trees and artificial neural networks, for example, are now being used  in various commercial and industrial applications. \u003cbr\u003e  Learning to Learn is an exciting new research direction within machine  learning. Similar to traditional machine-learning algorithms, the  methods described in \u003cem\u003eLearning to Learn\u003c\/em\u003e induce general functions  from experience. However, the book investigates algorithms that can  change the way they generalize, i.e., practice the task of learning  itself, and improve on it. \u003cbr\u003e  To illustrate the utility of learning to learn, it is worthwhile  comparing machine learning with human learning. Humans encounter a  continual stream of learning tasks. They do not just learn concepts or  motor skills, they also learn \u003cem\u003ebias\u003c\/em\u003e, i.e., they learn how to  generalize. As a result, humans are often able to generalize correctly  from extremely few examples - often just a single example  suffices to teach us a new thing. \u003cbr\u003e  A deeper understanding of computer programs that improve their ability  to learn can have a large practical impact on the field of machine  learning and beyond. In recent years, the field has made significant  progress towards a theory of learning to learn along with practical  new algorithms, some of which led to impressive results in real-world  applications. \u003cbr\u003e  \u003cem\u003eLearning to Learn\u003c\/em\u003e provides a survey of some of the most exciting  new research approaches, written by leading researchers in the field.  Its objective is to investigate the utility and feasibility of  computer programs that can learn how to learn, both from a practical  and a theoretical point of view.\u003c\/p\u003e \u003ch3\u003eDetails\u003c\/h3\u003e \u003cp\u003ePublished by: Springer\u003c\/p\u003e \u003cp\u003ePublication Date: 2012-10-04\u003c\/p\u003e \u003cp\u003eFormat: Paperback\u003c\/p\u003e \u003cp\u003e ISBN-10: 9781461375272\u003c\/p\u003e \u003cp\u003eISBN-13: 9781461375272\u003c\/p\u003e \u003cp\u003eDOI: 10.1007\/978-1-4615-5529-2\u003c\/p\u003e \u003cp\u003eDimensions: 235cm x155cm\u003c\/p\u003e \u003cp\u003ePages: 354\u003c\/p\u003e ","brand":"Springer","offers":[{"title":"Default Title","offer_id":44358761283724,"sku":"9781461375272","price":225.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9781461375272.jpg?v=1755113567","url":"https:\/\/lateknightbooks.com\/products\/9781461375272","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}