张会昌

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张会昌 关注的课程

Data Mining (MIT OCW) 0 个评论 关注

开始时间: 01/01/2014 持续时间: 未知

主页: http://ocw.mit.edu/courses/sloan-school-of-management/15-062-data-mining-spring-2003

简介: Data that has relevance for managerial decisions is accumulating at an incredible rate due to a host of technological advances. Electronic data capture has become inexpensive and ubiquitous as a by-product of innovations such as the internet, e-commerce, electronic banking, point-of-sale devices, bar-code readers, and intelligent machines. Such data is often stored in data warehouses and data marts specifically intended for management decision support. Data mining is a rapidly growing field that is concerned with developing techniques to assist managers to make intelligent use of these repositories. A number of successful applications have been reported in areas such as credit rating, fraud detection, database marketing, customer relationship management, and stock market investments. The field of data mining has evolved from the disciplines of statistics and artificial intelligence.

Big Data in Education (Coursera) 0 个评论 关注

开始时间: 待定 持续时间: Unknown

主页: https://www.coursera.org/course/bigdata-edu

简介: Education is increasingly occurring online or in educational software, resulting in an explosion of data that can be used to improve educational effectiveness and support basic research on learning. In this course, you will learn how and when to use key methods for educational data mining and learning analytics on this data.

Web Intelligence and Big Data (Coursera) 3 个评论 关注

开始时间: 04/20/2014 持续时间: 9 weeks

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

简介: This course is about building 'web-intelligence' applications exploiting big data sources arising social media, mobile devices and sensors, using new big-data platforms based on the 'map-reduce' parallel programming paradigm. During the fall semester this course is offered at the Indian Institute of Technology Delhi as well as the Indraprastha Institute of Information Technology Delhi.

Core Concepts in Data Analysis (Coursera) 0 个评论 关注

开始时间: 待定 持续时间: Unknown

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

简介: Learn both theory and application for basic methods that have been invented either for developing new concepts – principal components or clusters, or for finding interesting correlations – regression and classification. This is preceded by a thorough analysis of 1D and 2D data.

Machine Learning (Coursera) 7 个评论 关注

开始时间: 待定 持续时间: Unknown

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

简介: Why write programs when the computer can instead learn them from data? In this class you will learn how to make this happen, from the simplest machine learning algorithms to quite sophisticated ones. Enjoy!

Mining Massive Datasets (Coursera) 1 个评论 关注

开始时间: 09/12/2015 持续时间: 7 weeks

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

简介: This class teaches algorithms for extracting models and other information from very large amounts of data. The emphasis is on techniques that are efficient and that scale well.

Pattern Discovery in Data Mining (Coursera) 1 个评论 关注

开始时间: 02/09/2015 持续时间: 4 weeks

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

简介: Learn the basic concepts of data mining and dive deep into pattern discovery methods and their applications.

Process Mining: Data science in Action (Coursera) 0 个评论 关注

开始时间: 10/07/2015 持续时间: 8 weeks

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

简介: Process mining is the missing link between model-based process analysis and data-oriented analysis techniques. Through concrete data sets and easy to use software the course provides data science knowledge that can be applied directly to analyze and improve processes in a variety of domains.

Cluster Analysis in Data Mining (Coursera) 0 个评论 关注

开始时间: 04/27/2015 持续时间: 4 weeks

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

简介: Learn how to take scattered data and organize it into groups, for use in many applications such as market analysis and biomedical data analysis, or taken as a pre-processing step for many data mining tasks.

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