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Probabilistic Graphical Models (Coursera) 5 个评论 关注

开始时间: 04/08/2013 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.

機器學習技法 (Machine Learning Techniques) (Coursera) 2 个评论 关注

开始时间: 11/10/2015 持续时间: 8 weeks

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

简介: The course extends the fundamental tools in "Machine Learning Foundations" to powerful and practical models by three directions, which includes embedding numerous features, combining predictive features, and distilling hidden features. [這門課將先前「機器學習基石」課程中所學的基礎工具往三個方向延伸為強大而實用的工具。這三個方向包括嵌入大量的特徵、融合預測性的特徵、與萃取潛藏的特徵。]

Introduction to Big Data with Apache Spark (edX) 1 个评论 关注

开始时间: 待定 持续时间: 5 weeks

主页: https://www.edx.org/course/introduction-big-data-apache-spark-uc-berkeleyx-cs100-1x

简介: Learn how to apply data science techniques using parallel programming in Apache Spark to explore big (and small) data.

Probabilistic Graphical Models Specialization (Coursera专项课程) 0 个评论 关注

开始时间: 04/23/2018 持续时间: Unknown

主页: https://www.coursera.org/specializations/probabilistic-graphical-models

简介: 斯坦福大学 Daphne Koller 教授的概率图模型专项课程系列(Probabilistic Graphical Models Specialization),作为Coursera上最早的几门课程之一,这门概率图模型课程的相当有难度,完成作业拿到证书还是很有挑战的,感兴趣的同学可以关注:Probabilistic Graphical Models-Master a new way of reasoning and learning in complex domains