使用A/B测试衡量Amazon Personalize推荐结果的有效性

{"type":"doc","content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"Original URL: "},{"type":"link","attrs":{"href":"https:\/\/amazonaws-china.com\/cn\/blogs\/machine-learning\/using-a-b-testing-to-measure-the-efficacy-of-recommendations-generated-by-amazon-personalize\/","title":"","type":null},"content":[{"type":"text","text":"https:\/\/aws.amazon.com\/cn\/blogs\/machine-learning\/using-a-b-testing-to-measure-the-efficacy-of-recommendations-generated-by-amazon-personalize\/"}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"基于机器学习（ML）的推荐系统早已不是什么新鲜概念，但开发这类系统仍是一项需要投入大量资源的任务。无论是训练与推理期间的数据管理，还是运营具备可扩展性的机器学习实时API端点，都着实令人头痛。"},{"type":"link","attrs":{"href":"https:\/\/amazonaws-china.com\/personalize","title":"","type":null},"content":[{"type":"text","text":"Amazon Personalize"}]},{"type":"text","text":" 将Amazon.com过去二十多年来使用的同一套机器学习技术体系交付至您手中，轻松将复杂的个性化功能引入到您的应用程序，且无需任何机器学习专业知识。当前，来自零售、媒体与娱乐、游戏、旅游乃至酒店等行业的无数客户都在使用Amazon Personalize为用户提供个性化的内容推荐服务。在Amazon Personalize的帮助下，您可以实现一系列常见用例，包括为用户提供个性化商品推荐、显示相似商品以及根据用户喜好对商品进行重新排序等。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}}]}