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Hands-On Recommendation Systems with Python
Recommendationsystemsareattheheartofalmosteveryinternetbusinesstoday;fromFacebooktoNet?ixtoAmazon.Providinggoodrecommendations,whetherit'sfriends,movies,orgroceries,goesalongwayindefininguserexperienceandenticingyourcustomerstouseyourplatform.Thisbookshowsyouhowtodojustthat.YouwilllearnaboutthedifferentkindsofrecommendersusedintheindustryandseehowtobuildthemfromscratchusingPython.Noneedtowadethroughtonsofmachinelearningtheory—you'llgetstartedwithbuildingandlearningaboutrecommendersasquicklyaspossible..Inthisbook,youwillbuildanIMDBTop250clone,acontent-basedenginethatworksonmoviemetadata.You'llusecollaborativefilterstomakeuseofcustomerbehaviordata,andaHybridRecommenderthatincorporatescontentbasedandcollaborativefilteringtechniquesWiththisbook,allyouneedtogetstartedwithbuildingrecommendationsystemsisafamiliaritywithPython,andbythetimeyou'refnished,youwillhaveagreatgraspofhowrecommendersworkandbeinastrongpositiontoapplythetechniquesthatyouwilllearntoyourownproblemdomains.
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- Summary
- Case study – Building a hybrid model
- Introduction
- Technical requirements
品牌：中圖公司
上架時間：2021-07-16 17:35:21
出版社：Packt Publishing
本書數字版權由中圖公司提供，并由其授權上海閱文信息技術有限公司制作發行
