Personalized recommendations were one of the hottest concepts of 2016 — 2017. Probably started with today’s headlines, circle on the Internet were taken up a “personalized” agitation, no matter what product, seems to add a personalized recommendation system can tremendously improve operational efficiency and conversion rates, especially in the content distribution, areas such as electricity, social practice was brilliant (weibo, all news portals, jingdong, visited have achieved good grades). Personalized recommendations have become a product infrastructure, and even now personalized recommendations have been upgraded to “artificial intelligence.”
This certification system explains the concept, application and algorithm principle of recommendation system, and introduces ali’s recommendation engine product RecEng in detail. Finally, through a micro project, let students build a recommendation system by hand. The whole process is divided into four parts: data upload, data preprocessing, recommendation system setting and test on-line. Students can refer to this experiment and apply what they have learned to practice in combination with their own business and needs.
Where exactly is “personalized recommendation”? This series mainly discusses the personalized recommendation system under the background of artificial intelligence. This is the first part of this series: “How to build a personalized recommendation system from 0 to 1?” , and will continue to share and discuss the optimization ideas and practices of personalized recommendation system.
Content List:
01 Concepts and Application Scenarios Of recommendation System This section describes the background, concepts, features, and application scenarios of the recommendation engine.
02 Principles of the Recommendation Engine This section describes common recommendation engine algorithms, and the principles, advantages and disadvantages of each algorithm.
03 RecEng This section describes the features, capabilities, and data model of RecEng.
04 RecEng Basic Operations This section describes the basic operations of the RecEng recommendation engine.
This paper introduces how to use the recommendation engine product RecEng to build a recommendation system to support the recommendation business needs of enterprises.
06 Experiment Manual: Set up the e-commerce recommendation system detailed experiment operation manual, take you step by step to complete the establishment of e-commerce recommendation system.
This paper introduces how to use the recommendation engine product RecEng to build a recommendation system to support the recommendation business needs of enterprises.
06 Experiment Manual: Set up the e-commerce recommendation system detailed experiment operation manual, take you step by step to complete the establishment of e-commerce recommendation system.