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SARS Covid 2的全球数据分析 网络抓取工具worldosmeters_scraper.exe从worldometers.info中获取所有数据，并每天创建所有国家/地区的today_worldwide_covid19_data.csv数据库。 然后， covid19_analysis_2.2.py分析所有数据。 该脚本有两种语言，希腊语和英语。 只需输入“ GR”（希腊）或“ EN”（英语）即可。 如果您想测试脚本，只需下载covid19_analysis_2.2.exe并运行它。 today_worldwide_covid19_data.csv每天更新。 与old_version的区别在于，现在您可以从.csv文件中的224检查每个国家或地区的统计信息而且您只需下载一次.exe，而不是每天都要下载的旧版本！ 输出： 资料来源

目录 1 - 1 - Unit 1- Introduction (3-23).mp4 1 - 2 - Unit 1, Part 1- (1) Data Basics (4-52).mp4 1 - 3 - Unit 1, Part 1- (2) Observational Studies and Experiments (4-44).mp4 1 - 4 - Unit 1, Part 1- (3) Sampling and Sources of Bias (7-53).mp4 1 - 5 - Unit 1, Part 1- (4) Experimental Design (2-59).mp4 1 - 6 - Unit 1, Part 1- (Spotlight) Random Sample Assignment (3-47).mp4 1 - 7 - Unit 1, Part 2- (1) Visualizing Numerical Data (12-57).mp4 1 - 8 - Unit 1, Part 2- (2) Measures of Center (5-17).mp4 .....

Bayesian Data Analysis, Third Edition Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, Donald B. Rubin CRC Press

Music Data Analysis Foundations and Applications 英文无水印pdf pdf使用FoxitReader和PDF-XChangeViewer测试可以打开

自动化qPCR数据分析 一个python脚本，用于自动化分析来自标准定量聚合酶链React测定的数据的过程。

Haskell Data Analysis Cookbook 英文版 Haskell Data Analysis Cookbook 英文版 Haskell Data Analysis Cookbook 英文版

This book will take you on a voyage through all the steps involved in data analysis. It provides synergy between Haskell and data modeling, consisting of carefully chosen examples featuring some of the most popular machine learning techniques. You will begin with how to obtain and clean data from various sources. You will then learn how to use various data structures such as trees and graphs. The meat of data analysis occurs in the topics involving statistical techniques, parallelism, concurrency, and machine learning algorithms, along with various examples of visualizing and exporting results. By the end of the book, you will be empowered with techniques to maximize your potential when using Haskell for data analysis. What You Will Learn Obtain and analyze raw data from various sources including text files, CSV files, databases, and websites Implement practical tree and graph algorithms on various datasets Apply statistical methods such as moving average and linear regression to understand patterns Fiddle with parallel and concurrent code to speed up and simplify time-consuming algorithms Find clusters in data using some of the most popular machine learning algorithms Manage results by visualizing or exporting data

分析使用了DataCo Global公司使用的供应链数据集。供应链数据集，允许使用机器学习算法和R软件。重要的注册活动领域包括：供应，生产，销售，商业分销，还允许将结构化数据与非结构化数据进行关联以生成知识。 DescriptionDataCoSupplyChain.csv DataCoSupplyChainDataset.csv tokenized_access_logs.csv

人力资源数据分析 使用Logistic回归对公司的人员流失进行HR数据分析。 一家名为XYZ的大公司在任何给定时间点都雇用大约4000名员工。 但是，每年约有15％的员工离开公司，并需要用就业市场上可用的人才库来代替。 管理层认为，这种流失率（员工自己离开或被解雇而离职）对公司不利，原因如下：•前雇员的项目被推迟，这使得他们难以按时完成任务，从而导致消费者和合作伙伴之间的声誉损失•为了招募新人才，必须维持相当大的部门•通常，必须对新员工进行工作培训和/或给予时间使其适应环境的培训因此，管理层已与人力资源分析公司签约，以了解他们应重点关注哪些因素，以减少人员流失。 换句话说，他们想知道应该对工作场所进行哪些更改，以使大多数员工留下来。 而且，他们想知道这些变量中的哪一个最重要，需要立即解决。 案例研究的目标：您需要使用逻辑回归模型对损耗的概率进行建模。 管理层将使用由此获得的结果来了解他