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所在平台: Udemy |
课程主页: https://www.udemy.com/course/learn-how-to-create-content-based-recommendations-for-hotel/
课程评论：没有评论
本Coursera课程教授如何利用基于内容的推荐系统构建酒店推荐引擎。课程面向初学者，将帮助学员掌握推荐系统的基础知识，包括不同类型的推荐系统、文本处理技术（如分词、停用词移除、n-grams）、TF-IDF向量化以及余弦相似度算法。 课程将通过Jupyter Notebook进行编程教学，学员将学习如何使用Python构建一个基于内容的推荐系统。重点内容包括： * 推荐系统的介绍 * 协同过滤的介绍 * 一步步在Jupyter Notebook中构建基于物品的协同过滤推荐系统 * 构建一个真实的音乐推荐Web应用程序 通过本课程，学员将能够： * 学习推荐系统知识，亲手构建一个真实的酒店推荐引擎。 * 掌握课程内容，并通过超过10个讲座视频进行学习。 * 适合初学者程序员，尤其擅长通过实践学习的学员。 * 采用可视化教学方法，提高学习效率和知识留存率。 * 将复杂的应用分解为简单的步骤进行讲解。 * 提供挑战性练习，巩固所学概念，并提供解决方案。 课程强调了推荐系统在信息检索、产品促销（upselling和cross-selling）方面的关键作用，并指出掌握基于内容的过滤技术将为学员在推荐系统开发领域提供显著优势。同时，课程也提到协同过滤（特别是SVD）是高需求技能，并列举了Google、Facebook、Microsoft、Airbnb、LinkedIn等大型公司在推荐系统方面的成功应用案例，以及它们如何通过推荐系统显著提升公司生产力。
Course DescriptionLearn to build a recommendation engine with Content-Based filtering Build a strong foundation in Content-Based Recommendation Systems with this tutorial for beginners.Understanding of recommendation systemsTypes of recommendation systemsTokenizationStop words removaln-grams TF-IDF VectorizerCosine similarity algorithmUser Jupyter Notebook for programmingA Powerful Skill at Your Fingertips Learning the fundamentals of a recommendation system puts a powerful and handy tool at your fingertips. Python and Jupyter are free, easy to learn, have excellent documentation.Jobs in the recommendation systems area are plentiful, and learning content-based filtering will give you a strong edge. Content-based filtering has the advantage of recommending articles when you have a new app or site, and there are no users yet for the site.Content-Based Recommendation Systems are becoming very popular. Amazon, Walmart, Google eCommerce websites are a few famous examples of recommendation systems in action. Recommendation Systems are vital in information retrieval, upselling, and cross-selling of products. Learning Collaborative filtering with SVD will help you become a recommendation system developer who is in high demand.Big companies like Google, Facebook, Microsoft, Airbnb, and Linked In are already using recommendation systems with content-based recommendations in information retrieval and social platforms. They claimed that using recommendation systems has boosted the productivity of the entire company significantly.Content and Overview This course teaches you how to build recommendation systems using open-source Python and Jupyter framework. You will work along with me step by step to build the following answers.Introduction to recommendation systems.Introduction to Collaborative filteringBuild a jupyter notebook step by step using item-based collaborative filteringBuild a real-world web application to recommend musicWhat am I going to get from this course?Learn recommendation systems and build a real-world hotel recommendation engine from a professional trainer from your own desk.Over 10 lectures teaching you how to build real-world recommendation systemsSuitable for beginner programmers and ideal for users who learn faster when shown.Visual training method, offering users increased retention and accelerated learning.Breaks even the most complex applications down into simplistic steps.Offers challenges to students to enable the reinforcement of concepts. Also, solutions are described to validate the challenges.
