计算广告学 (CourseraArchive) 5 个评论 关注

开始时间: 04/22/2022 持续时间: 8 weeks

主页: http://study.163.com/course/courseMain.htm?courseId=321007

简介: 本课程从计算广告各个阶段所遇到的市场挑战为出发点，清晰解释了广告市场纷繁复杂的产品逻辑，并且对其中的关键技术和算法做了深入的探讨。依次介绍了合约广告系统(Agreement-based Advertising)，竞价广告系统(Auction-based Advertising)，广告交易市场(Ad Exchange)等重要课题。

Machine Learning (CourseraArchive) 29 个评论 关注

开始时间: 04/22/2022 持续时间: Unknown

主页: https://www.coursera.org/course/ml

简介: Learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself.

Probabilistic Graphical Models (CourseraArchive) 5 个评论 关注

开始时间: 04/22/2022 持续时间: 11 weeks

主页: https://www.coursera.org/course/pgm

简介: In this class, you will learn the basics of the PGM representation and how to construct them, using both human knowledge and machine learning techniques.

Information Theory (CourseraArchive) 1 个评论 关注

开始时间: 04/22/2022 持续时间: Unknown

主页: https://www.coursera.org/course/informationtheory

简介: This course is an introduction to information theory, which emphasizes fundamental concepts as well as analytical techniques. Specific topics include: Information Measures, The I-Measure, Zero-Error Data Compression, Weak Typicality, Strong Typicality, Discrete Memoryless Channels, etc.

Introduction to Recommender Systems (CourseraArchive) 3 个评论 关注

开始时间: 04/22/2022 持续时间: Unknown

主页: https://www.coursera.org/course/recsys

简介: This course introduces the concepts, applications, algorithms, programming, and design of recommender systems--software systems that recommend products or information, often based on extensive personalization. Learn how web merchants such as Amazon.com personalize product suggestions and how to apply the same techniques in your own systems!