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Lynda – Data Science Foundations: Data Mining

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Lynda - Data Science Foundations: Data Mining
Lynda - Data Science Foundations: Data Mining
Size: 634 MB | Duration: 4h 41m | Video: AVC (.mp4) 1280x720 15&30fps | Audio: AAC 48KHz 2ch
Genre: eLearning | Level: Intermediate | Language: English

All data science begins with good data. Data mining is a framework for collecting, searching, and filtering raw data in a systematic matter, ensuring you have clean data from the start. It also helps you parse large data sets, and get at the most meaningful, useful information. This course, Data Science Foundations: Data Mining, is designed to provide a solid point of entry to all the tools, techniques, and tactical thinking behind data mining. Barton Poulson covers data sources and types, the languages and software used in data mining (including R and Python), and specific task-based lessons that help you practice the most common data-mining techniques: text mining, data clustering, association analysis, and more. This course is an absolute necessity for those interested in joining the data science workforce, and for those who need to obtain more experience in data mining.

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  1. Lynda - 数据科学基础:数据矿藏 所有的数据科学开始于好的数据。数据挖掘是一个以系统化的方式用于收集、搜索和筛选原始数据的框架,从而能够确保你从一开始就拥有干净的数据。它还可以帮助你解析大数据集,从中获取最有意义和有用的信息。本教程为数据挖掘背后所有的工具、技术以及策略性思维提供了一个坚实的切入点。Barton Poulson会讲到数据源和类型、用于数据挖掘的语言和软件(包括R和Python),以及特殊的基于任务的内容,从而帮助你联系最常见的数据挖掘技术:文本挖掘、数据集群以及相关联分析等。本教程对于那些打算在数据科学领域发展的人,以及想要获得更多经验的人绝对是必看的。 主要内容:数据挖掘的预先准备;数据挖掘使用R、Python、Orange以及RapidMinder;数据变形;数据集群;异常检测;关联分析;回归分析;序列挖掘;文本挖掘。
    wilde(特殊组-翻译)1年前 (2016-09-08)