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所在平台: Udemy |
课程主页: https://www.udemy.com/course/advanced-r/
课程评论：没有评论
课程名称：高级R 课程概述：本课程面向R和数据科学专业人士，旨在帮助他们掌握R语言。无论是中级还是高级用户，都能从本课程中分离出来，与其他使用R进行分析的人有所区别。该课程不推荐给初学者。我们首先介绍闭包、环境、日期等更高级的主题。接着，我们探讨正则表达式和HTML数据解析。课程还讲解了如何编写R包，以及如果想将代码上传至R的库，CRAN团队所期望的文档编写方式。随后，我们介绍了代码剖析的必要技能，并深入到C++和Rcpp的内容，展示如何编写使用OpenMP的超级高速C++并行代码。掌握Rcpp将使您的R技能达到一个新高度。与同事在使用R函数时，您将能够运行速度快4-8倍的Rcpp+OpenMP等效代码。 接下来，我们将介绍Python和Java，并展示如何从R调用这些语言，反之亦然。这对于编写利用这对语言出色的面向对象特性代码非常有帮助。您将能够在Java或Python中构建自己的类，以存储从R获取的数据。鉴于Python社区快速发展和众多优秀包的涌现，能够直接从R调用任何Python包中的函数将是一个巨大的优势。 最后，我们讲解如何使用sqldf，这是一个在R中进行严肃的生产级数据处理的优秀包。尽管它有一些限制，我们将能够直接在R中编写SQL查询，并展示如何使用特定技巧绕过这些限制，例如其无法执行完全连接的问题。课程中使用的所有代码（R、Java、C++、.csv）均可下载，所有讲座也可以下载。我们的教学策略是提供尽量简单的示例，以便您可以轻松跟随每节课。若您有任何疑问或意见，请随时与我们联系。
This course is intended for R and data science professionals aiming to master R. Intermediate and advanced users, will both find that this course will separate them from the rest of people doing analytics with R. We don't recommend this course on beginners. We start by explaining how to work with closures, environments, dates, and more advanced topics. We then move into regex expressions and parsing html data. We explain how to write R packages, and write the proper documentation that the CRAN team expects if you want to upload your code into R's libraries. After that we introduce the necessary skills for profiling your R code. We then move into C++ and Rcpp, and we show how to write super fast C++ parallel code that uses OpenMP. Understanding and mastering Rcpp will allow you to push your R skills to another dimension. When your colleagues are writing R functions, you will be able to get Rcpp+OpenMP equivalent code running 4-8X times faster. We then move into Python and Java, and show how these can be called from R and vice-versa. This will be really helpful for writing code that leverages the excellent object oriented features from this pair of languages. You will be able to build your own classes in Java or Python that store the data that you get from R. Since the Python community is growing so fast, and producing so wonderful packages, it's great to know that you will be able to call any function from any Python package directly from R. We finally explain how to use sqldf, which is a wonderful package for doing serious, production grade data processing in R. Even though it has its limitations, we will be able to write SQL queries directly in R. We will certainly show how to bypass those limitations, such as its inability to write full joins using specific tricks. All the code (R,JAVA,C++,.csv) used in this course is available for download, and all the lectures can be downloaded as well. Our teaching strategy is to present you with examples carrying the minimal complexity, so we hope you can easily follow each lecture. In case you have doubts or comments, feel free to send us a message
