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Unsupervised Machine Learning(으)로 돌아가기

IBM 기술 네트워크의 Unsupervised Machine Learning 학습자 리뷰 및 피드백

137개의 평가

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


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.


2021년 7월 5일

Great course. Maybe there is one instance of wrong answer in one of the quizzes. Everything elese is perfect. Thanks IBM !

필터링 기준:

Unsupervised Machine Learning의 32개 리뷰 중 1~25

교육 기관: Anish D

2021년 4월 19일

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.

교육 기관: Abdillah F

2020년 11월 7일

Great course and very well structured. I'm really impressed with the instructor who give thorough walkthrough to the code.

교육 기관: Hossam G M

2021년 10월 4일

This course is great from a coding and final project point of view. in this course I learned how to explore the different techniques and algorithms available to cluster unlabeled data. the notebook and videos are very great too. they walk you through the coding prospective step by step. but from the theory point of view, it is hard to well understand it well in these videos. you have to be aware of them first or study them on your own. although the quizzes aren't that much indicative about understanding. they need to be tougher and contain more questions. the last thing we should be provided the lecture sildes.

교육 기관: Ashish P

2021년 3월 13일

Very Well Structured, concepts clearly explained, lots of Labs to get a hands-on practice and in the end a summary of all the key points explained.

A couple of Labs for DBSCAN and Mean-Shift would have been great.

The concept of SVD with the matrices was not very clear from the videos. Maybe some detailed notes on how the matrices are divided into the submatrices could be really helpful.

교육 기관: Léa Z

2021년 4월 18일

As usual with IBM courses, the concepts are well explained and the split between theory and demo on python is very useful. However in this specific course there are a LOT of mistakes in graded tests, which have been spotted by users for months but are unanswered by course owners in discussion forums. It is a shame, and hopefully the last two modules of the professional certification are benefitting from a better maintenance.

교육 기관: az

2022년 5월 10일

Many typos and incorrect quizzes that haven't been fixed after several years.

교육 기관: Sid C

2022년 4월 5일

This course enabled me to further develop my standard work process in performing Machine Learning activities. It also expanded my existing skills set with the addition of Unsupervised Machine Learning methods --this actually significantly improved my model performances.

교육 기관: SMRUTI R D

2021년 9월 20일

I found the learning experience extremely good and absorbing. The approach of the program to impart theoritical background of algorithms before taking of Labs is very helpful. Also, after the course one gets a broad view of the contexts behind different approaches.

교육 기관: Alparslan T

2022년 1월 6일

Excellent course on unsupervised ML. Clustering, dimensionality reduction and even classification are very well explained and practiced with high level coding on Python. Thanks IBM.

교육 기관: anand v

2021년 7월 6일

G​reat course. Maybe there is one instance of wrong answer in one of the quizzes. Everything elese is perfect. Thanks IBM !


2021년 5월 22일

Sometimes so fast, but it motives to research more and more about ML.

교육 기관: george s

2021년 9월 3일

Excellent course! Just examples of clustering could be a bit better.

교육 기관: Marwan K

2022년 2월 22일

T​hank you Coursera.

T​hank you IBM.

T​hank you to all instructors.

교육 기관: Luis P S

2021년 6월 2일

E​xcellent!! Easy and good way to learn unsupervised algorithms!

교육 기관: My B

2021년 4월 23일

A high quality course with lots of practical techniques

교육 기관: Nikolas R W

2020년 12월 26일

Great course for learning about Unsupervised Learning

교육 기관: Krishnendu D

2022년 4월 11일

Awesome and wholesome explaination of the concepts

교육 기관: Jose M

2021년 1월 25일

Again, congrats to the instructor on the videos.

교육 기관: Saraswati P

2021년 10월 23일

W​ell structured course with many examples

교육 기관: Veronica A T S

2021년 6월 27일

i wouuld have liked a notebook on dbscan

교육 기관: Volodymyr

2021년 8월 5일

Well balanced course, I recommend

교육 기관: Wissam Z

2021년 10월 10일

Very Professional course

교육 기관: Uğur K

2020년 8월 23일

Very tidy explanations

교육 기관: Bernard F

2021년 1월 26일

An excellent course!

교육 기관: Simeon M

2021년 9월 14일