강좌 소개
This course introduces you to one of the main types of Machine Learning: Unsupervised Learning. You will learn how to find insights from data sets that do not have a target or labeled variable. You will learn several clustering and dimension reduction algorithms for unsupervised learning as well as how to select the algorithm that best suits your data. The hands-on section of this course focuses on using best practices for unsupervised learning.
By the end of this course you should be able to:
Explain the kinds of problems suitable for Unsupervised Learning approaches
Explain the curse of dimensionality, and how it makes clustering difficult with many features
Describe and use common clustering and dimensionality-reduction algorithms
Try clustering points where appropriate, compare the performance of per-cluster models
Understand metrics relevant for characterizing clusters
Who should take this course?
This course targets aspiring data scientists interested in acquiring hands-on experience with Unsupervised Machine Learning techniques in a business setting.
What skills should you have?
To make the most out of this course, you should have familiarity with programming on a Python development environment, as well as fundamental understanding of Data Cleaning, Exploratory Data Analysis, Calculus, Linear Algebra, Probability, and Statistics.
최상위 리뷰
AD
2021년 4월 18일
It is a beautifully crafted course that looks at various clustering algorithms. More importantly, show the pros and cons of each algorithm/technique based on different patterns.
AF
2020년 11월 6일
Great course and very well structured. I'm really impressed with the instructor who give thorough walkthrough to the code.
필터링 기준:
Unsupervised Machine Learning의 31개 리뷰 중 26~31
교육 기관: Cui Y
•2022년 1월 13일
Thank you!
교육 기관: Fernandes M R
•2021년 3월 10일
very good
교육 기관: Kaumil A
•2021년 2월 26일
Awesome
교육 기관: Keyur U
•2020년 12월 24일
They have got the best instructor!
교육 기관: Tech S
•2021년 9월 2일
No math , only superficial concepts. Not recommending to anyone else..
교육 기관: az
•2022년 5월 10일
Many typos and incorrect quizzes that haven't been fixed after several years.
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