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所在平台: Udemy |
课程主页: https://www.udemy.com/course/robust-data-analysis-in-r-and-matlab/
课程评论：没有评论
课程名称：R和Matlab中的异常值高级分析 课程概述：在统计学、数据分析、数据挖掘、机器学习、人工智能以及模式识别等领域，稳健的数据分析和异常值检测至关重要。该课程提供关于异常值的FREE BOOK，包含具体的技巧和策略，以及所有稳健检测方法的总结，帮助学员获得准确的结果和出色的数据分析能力。研究人员、学生、数据分析师及任何处理真实数据的人都需要了解异常值问题，并掌握如何应对这一问题以及应使用哪些稳健的方法。 课程强调，绝大多数机器学习算法能够检测到大多数数据的共性特征，但往往会困惑或忽略那些不寻常的数据。在关乎人们安全的情况下，如医疗数据分析、物联网(IoT)的世界、公司风险和安全等情境下，这些异常数据不应被忽视。课程通过案例探讨了如果忽视异常信号可能导致的严重后果，例如疫情的爆发或者天然气泄漏等紧急情况。 通过课程，学员将成为稳健数据分析的专家，掌握处理异常数据的理论概念，并具备使用两种编程语言（R-Studio和Matlab）实施算法的能力。学员将加入一个在线社区，可以向其他学生提问，讨论异常值分析。此外，课程提供的示例代码可在开放的GitHub库中下载使用，并且包含基本概念的介绍，帮助学员回顾必要的知识以理解异常值检测方法。 本课程旨在帮助学员理解并应对学术、工业和数据分析及机器学习领域中一个重要的主题，通过实例帮助学员可视化异常值分析的重要性，并指导他们自主进行相关分析。
Robust data analysis and outlier detection are crucial in Statistics, Data Analysis, Data Mining, Machine Learning, Artificial Intelligence, Pattern Recognition, Classification, Principal Components, Regression, Big Data, and any field related to the data.With the course you will obtain the FREE BOOK ABOUT OUTLIERS with specific tips and tricks, and the summary of all the robust methods to detect them that will help you obtain accurate results and awsome data analysis.Researchers, students, data analysts, and mostly anyone dealing with real data, should be aware of the problem with outliers (and outliers) and should know how to deal with this problem and what robust methods should be used.. The vast majority of Machine Learning algorithms are capable of detecting characteristics common to the majority of data, but many times they are confused or even ignore those atypical data, which should not be ignored in conditions where the security of people, such as the analysis of medical data, the world of the Internet of Things IoT, or risks and security in companies.What would happen if a virus spread throughout the world because we ignored anomalous data? We would have a pandemic, like that of COVID19, which if the outlier signals detected by neural networks had not been ignored, we could have acted upon beforehand.What would happen if we ignored any signal from a Smart City system? We could miss a gas leak.What would happen if by ignoring an alarm, we miss a meteorite coming towards the earth? We would have to call Bruce Willis, to save us from Armageddon.With this course you will be an expert in robust data analysis, in the detection and treatment of atypical data, both learning the theoretical concepts, and having at your disposal the algorithms implemented in a practical way with two different languages so that you can choose the one that best suits you: R-Studio and Matlab.You will also have access to a community for questions, where all the students are and you can ask what you want about the analysis of outliers.The example implementation codes are available to you in the open Github repository for you to download and use.In addition, we have two sections of basic concepts that will help you to remember some notions necessary to understand atypical detection methods.With this course you will be able to understand and know how to deal with one of the most important topics of today both academically, in the industry and in data analysis or machine learning. The examples will help you to visualize the importance of the analysis of outliers as well as a guide to carry out these analyzes yourself.
