{"product_id":"9781785883538","title":"Building Recommendation Engines","description":"\u003cp\u003e\u003cb\u003eUnderstand your data and user preferences to make intelligent, accurate, and profitable decisions\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eAbout This Book\u003c\/b\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eA step-by-step guide to building recommendation engines that are personalized, scalable, and real time\u003c\/li\u003e\n\u003cli\u003eGet to grips with the best tool available on the market to create recommender systems\u003c\/li\u003e\n\u003cli\u003eThis hands-on guide shows you how to implement different tools for recommendation engines, and when to use which\u003c\/li\u003e\n\u003c\/ul\u003e\u003cb\u003eWho This Book Is For\u003c\/b\u003e\u003cp\u003eThis book caters to beginners and experienced data scientists looking to understand and build complex predictive decision-making systems, recommendation engines using R, Python, Spark, Neo4j, and Hadoop.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eWhat You Will Learn\u003c\/b\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eBuild your first recommendation engine\u003c\/li\u003e\n\u003cli\u003eDiscover the tools needed to build recommendation engines\u003c\/li\u003e\n\u003cli\u003eDive into the various techniques of recommender systems such as collaborative, content-based, and cross-recommendations\u003c\/li\u003e\n\u003cli\u003eCreate efficient decision-making systems that will ease your work\u003c\/li\u003e\n\u003cli\u003eFamiliarize yourself with machine learning algorithms in different frameworks\u003c\/li\u003e\n\u003cli\u003eMaster different versions of recommendation engines from practical code examples\u003c\/li\u003e\n\u003cli\u003eExplore various recommender systems and implement them in popular techniques with R, Python, Spark, and others\u003c\/li\u003e\n\u003c\/ul\u003e\u003cb\u003eIn Detail\u003c\/b\u003e\u003cp\u003eA recommendation engine (sometimes referred to as a recommender system) is a tool that lets algorithm developers predict what a user may or may not like among a list of given items. Recommender systems have become extremely common in recent years, and are applied in a variety of applications. The most popular ones are movies, music, news, books, research articles, search queries, social tags, and products in general.\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eThe book starts with an introduction to recommendation systems and its applications. You will then start building recommendation engines straight away from the very basics. As you move along, you will learn to build recommender systems with popular frameworks such as R, Python, Spark, Neo4j, and Hadoop. You will get an insight into the pros and cons of each recommendation engine and when to use which recommendation to ensure each pick is the one that suits you the best.\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eDuring the course of the book, you will create simple recommendation engine, real-time recommendation engine, scalable recommendation engine, and more. You will familiarize yourselves with various techniques of recommender systems such as collaborative, content-based, and cross-recommendations before getting to know the best practices of building a recommender system towards the end of the book!\u003c\/p\u003e\u003cp\u003e\u003cb\u003eStyle and approach\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003eThis book follows a step-by-step practical approach where users will learn to build recommendation engines with increasing complexity in every chapter\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e","brand":"Packt Publishing","offers":[{"title":"Default Title","offer_id":47163676754160,"sku":"9781785883538","price":39.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0737\/7593\/9824\/files\/9781785883538_p0.jpg?v=1763728807","url":"https:\/\/shop-qa.barnesandnoble.com\/products\/9781785883538","provider":"Barnes \u0026 Noble (DEV)","version":"1.0","type":"link"}