課程資料
報名日期
全年招生
課程級別
學習模式
修業期
5 小時 34 分鐘
教學語言
英語
授課導師
Rajat Raj Aggarwal
證書
- 可獲發
- *證書的發放與分配，依課程提供者的政策及安排而定。
評分
2次瀏覽
課程簡介
learn the basics of clustering and R
This course would get you started with clustering, which is one of the most well known machine learning algorithm, Anyone looking to pursue a career in data science can use the clustering concepts and techniques taught in this course to gain the necessary skill for processing and clustering any form of data. In addition, the course would familiarize you with R, which is becoming the default programming language for processing data among the global companies.
課程章節
- 7 個章節
- 42 堂課
- 第 1 章 Course Preview, Understanding the Basics of Clustering
- 第 2 章 Popular distance Measure - Euclidean & Hamming/ Kmeans Clustering in R
- 第 3 章 Understand Partitioning Around Medoids, Hierarchical form of Clustering
- 第 4 章 Understand clustering process of binary data, Kmodes clustering
- 第 5 章 Density-based clustering, cluster ordinal data, find replacement for empty cell
- 第 6 章 Determine ideal number of clusters, daisy function to cluster mixed data
- 第 7 章 Goodbye
課程內容
- Basics of clustering and R, various clustering techniques, Machine Learning
評價
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HHannu Koistinen
Proper English would be more appropriate. Not that Indian accent!!!
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AAnnonymous Person
I thought of being mean and adding 1star until you add a lesson 6.1 for how to manually choose which variable is base or descriptive e.g. is churn 1/0 a base or descriptive and is rating 1 to 10 a base or descriptive? I feel they can be both depending on situation? If so please add a lesson to tell us how to label the variable with examples for different situations, this topic confuses me. Thank you sir.
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BBrendon Cassar
Material was interesting, extensive and carefully explained. Delivery a bit monotonous at times but gets the job done
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IIan Greener
Very clear, especially in early examples. I would have liked a little more on the daisy function, and there are a couple of small presentational errors. Other than that, very good.
