种子简介

种子名称： Lynda - Data Science Foundations: Data Mining
文件类型： 视频
文件数目： 54个文件
文件大小： 616.65 MB
收录时间： 2017-2-17 21:47
已经下载： 3次
资源热度： 135
最近下载： 2024-12-26 14:02

下载BT种子文件

下载Torrent文件(.torrent) 立即下载

磁力链接下载

magnet:?xt=urn:btih:2b2db98b60882e3bb0bb2a5ad61f93eb82c82608&dn=Lynda - Data Science Foundations: Data Mining 复制链接到迅雷、QQ旋风进行下载，或者使用百度云离线下载。

喜欢这个种子的人也喜欢

种子包含的文件

Lynda - Data Science Foundations: Data Mining.torrent

053 Text mining in RapidMiner.mp420.04MB

028 Anomaly detection in Python.mp411.06MB

048 Sequence mining in BigML - Part 2.mp49.85MB

045 Sequence mining in R.mp413.39MB

034 Association analysis in Python.mp45.24MB

044 Sequence mining algorithms.mp47.24MB

019 Classification goals.mp46.31MB

032 Association analysis data.mp46.15MB

006 Software prerequisites.mp411.75MB

042 Regression analysis in RapidMiner.mp410.16MB

024 Classification in KNIME.mp416.06MB

046 Sequence mining in Python.mp49.94MB

007 Goals of data reduction.mp49.87MB

038 Regression analysis data.mp46.58MB

049 Text mining goals.mp45.02MB

004 Data mining prerequisites.mp45.74MB

031 Association analysis goals.mp410.11MB

050 Text mining algorithms.mp44.96MB

018 Clustering in Orange.mp414.85MB

037 Regression analysis goals.mp45.48MB

015 Clustering in R.mp414.44MB

041 Regression analysis in KNIME.mp46.86MB

020 Classification data.mp411.64MB

003 Exercise files.mp41.58MB

021 Classification in R.mp430.6MB

012 Data reduction in RapidMiner.mp419.62MB

047 Sequence mining in BigML - Part 1.mp48.75MB

008 Data for data reduction.mp47.82MB

013 Clustering goals.mp46.07MB

023 Classification in RapidMiner.mp420.12MB

039 Regression analysis in R.mp410.71MB

022 Classification in Python.mp48.69MB

002 Who should watch this course.mp41.71MB

054 Next steps.mp44.57MB

027 Anomaly detection in R.mp425.86MB

052 Text mining in Python.mp421.62MB

043 Sequence mining goals.mp43.92MB

051 Text mining in R.mp424.05MB

001 Welcome.mp45.58MB

016 Clustering in Python.mp46.7MB

036 Association analysis in KNIME.mp414.61MB

005 Algorithm prerequisites.mp45.76MB

011 Data reduction in Orange.mp49.94MB

009 Data reduction in R.mp423.22MB

029 Anomaly detection in BigML.mp413.31MB

017 Clustering in BigML.mp429.65MB

026 Anomaly detection data.mp410.51MB

033 Association analysis in R.mp422.12MB

030 Anomaly detection in RapidMiner.mp411.02MB

014 Clustering data.mp49.11MB

035 Association analysis in Orange.mp411.82MB

040 Regression analysis in Python.mp48.34MB

010 Data reduction in Python.mp48.63MB

025 Anomaly detection goals.mp47.9MB