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所在平台: Udemy |
课程主页: https://www.udemy.com/course/building-real-world-books-recommendation-engine-with-python/
课程评论：没有评论
**课程名称：** 使用Python构建真实世界的图书推荐引擎 **课程概述：** 本课程将带领初学者打下坚实的推荐系统基础。您将学习如何利用协同过滤和Python这一流行编程语言来构建推荐引擎。课程重点包括： * 理解推荐系统的基本原理。 * 掌握如何利用协同过滤进行文档分类。 * 运用Jupyter Notebook进行编程实践。 * 使用奇异值分解（SVD）来构建推荐引擎。 **为什么要学习推荐系统？** 推荐系统是一项日益重要且需求旺盛的技能。Amazon、Walmart、Google等众多知名企业都在广泛应用推荐系统，这在信息检索、产品增销和交叉销售方面发挥着至关重要的作用。掌握协同过滤和SVD将为您在竞争激烈的就业市场中带来显著优势。Google、Facebook、Microsoft、AirBnB和Linked In等大公司都通过Item-based Collaborative Filtering在信息检索和社会平台中取得显著成效。 **课程内容与结构：** 本课程将使用开源Python和Jupyter框架，一步步指导您完成以下内容的学习和实践： * 推荐系统入门。 * 协同过滤入门。 * 使用Item-based Collaborative Filtering构建Jupyter Notebook。 * 构建一个实际的图书推荐Web应用程序。 **您将收获什么？** * 从专业培训师那里学会推荐系统知识，并亲手构建一个真实的图书推荐引擎。 * 超过10个教学环节，涵盖真实世界推荐系统的构建过程。 * 适合初学者，尤其适合通过实践学习的用户。 * 采用直观的视觉化教学方法，提高学习效率和知识记忆。 * 将复杂的应用分解为简单的步骤进行讲解。 * 提供练习挑战和对应的解决方案，以巩固所学知识。 **备注：** 尽管示例中使用短文档，但本课程的代码也可用于长文档。
Course DescriptionLearn to build recommendation engine with Collaborative filtering and popular programming language Python.Build a strong foundation in Recommendation Systems with this tutorial for beginners.Understanding of recommendation systemsLeverage Collaborative filtering to classify documentsUser Jupyter Notebook for programmingUse singular value decomposition (SVD) for recommendation engineA Powerful Skill at Your Fingertips Learning the fundamentals of recommendation system puts a powerful and very useful tool at your fingertips. Python and Jupyter are free, easy to learn, has excellent documentation.Jobs in recommendation systems area are plentiful, and being able to learn Collaborative filtering and SVD will give you a strong edge.Recommendation Systems ares becoming very popular. Amazon, Walmart, Google eCommerce websites are few famous example 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 which is in high demand.Big companies like Google, Facebook, Microsoft, AirBnB and Linked In already using recommendation systens with item based collaborative in information retrieval and social platforms. They claimed that using recommendation systems has boosted productivity of entire company significantly.Content and Overview This course teaches you on how to build recommendation systems using open source Python and Jupyter framework. You will work along with me step by step to build following answersIntroduction to recommendation systems.Introduction to Collaborative filteringBuild an jupyter notebook step by step using item based collaborative filteringBuild a real world web application to recommend booksWhat am I going to get from this course?Learn recommendations systems and build real world books recommendation engine from 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 reinforcement of concepts. Also solutions are described to validate the challenges.Note: Please note that I am using short documents in this example to illustrate concepts. You can use same code for longer documents as well.
