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所在平台: Udemy |
课程主页: https://www.udemy.com/course/applied-unsupervised-learning-with-r/
课程评论：没有评论
课程名称：应用无监督学习与R 课程概述： 《应用无监督学习与R》是一个从基础开始的课程，旨在教授聚类方法、分布分析、数据编码器及R语言的特点，帮助你更好地理解数据，并解决重要的商业问题。课程首先介绍最重要、应用最广泛的无监督学习方法——聚类，详细讲解三种主要的聚类算法：k-均值聚类、分裂聚类和凝聚聚类。随后，课程将学习市场篮子分析、核密度估计、主成分分析和异常检测。这些方法将通过R编写的代码进行介绍，并提供关于如何操作、编辑和改进R代码的进一步指导。 为了帮助学生获得实际的理解，课程还提供了将这些方法应用于真实商业问题的实用技巧，包括市场细分和欺诈检测。通过有趣的活动，学生将探索数据编码器和潜在变量模型。到课程结束时，学员将对不同的异常检测方法（例如离群点检测、马哈拉诺比斯距离、上下文和集体异常检测）有更深入的理解。 关于讲师： 阿洛克·马利克是一位来自印度的数据科学家，曾在金融、加密货币交易、物流和自然语言处理等领域创建和部署无监督学习解决方案。他在贾巴尔普尔的印度信息技术设计与制造学院获得了电子与通信工程的技术学士学位。 布拉德福德·塔克菲尔德为多个行业的公司设计并实施数据科学解决方案。他的学士学位为数学，博士学位为经济学，曾在学术期刊和大众媒体上发表关于线性代数、心理学和公共政策的文章。 伯特·戈尔尼克拥有航空航天工程文凭，并追求经济学硕士学位，拥有10年的R语言经验，是一名数据科学家及在线数据科学和机器学习的培训师。
Starting with the basics, Applied Unsupervised Learning with R explains clustering methods, distribution analysis, data encoders, and features of R that enable you to understand your data better and get answers to your most pressing business questions. This course begins with the most important and commonly used method for unsupervised learning - clustering - and explains the three main clustering algorithms - k-means, divisive, and agglomerative. Following this, you'll study market basket analysis, kernel density estimation, principal component analysis, and anomaly detection. You'll be introduced to these methods using code written in R, with further instructions on how to work with, edit, and improve R code. To help you gain a practical understanding, the course also features useful tips on applying these methods to real business problems, including market segmentation and fraud detection. By working through interesting activities, you'll explore data encoders and latent variable models. By the end of this course, you will have a better understanding of different anomaly detection methods, such as outlier detection, Mahalanobis distances, and contextual and collective anomaly detection.About the AuthorAlok Malik is a data scientist based in India. He has previously worked on creating and deploying unsupervised learning solutions in fields such as finance, cryptocurrency trading, logistics, and natural language processing. He has a bachelor's degree in technology from the Indian Institute of Information Technology, Design and Manufacturing, Jabalpur, where he studied electronics and communication engineering.Bradford Tuckfield has designed and implemented data science solutions for firms in a variety of industries. He studied math for his bachelor's degree and economics for his Ph.D. He has written for scholarly journals and the popular press, on topics including linear algebra, psychology, and public policy.Bert Gollnick is a Diploma in Aerospace Engineering and has pursued MSc in Economics.He is also a Data Scientist and has 10 years experience in R. He is also an online trainer for Data Science and Machine Learning.
