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Avis et commentaires pour d'étudiants pour Unsupervised Machine Learning par Réseau de compétences IBM

4.7
étoiles
138 évaluations

À propos du cours

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....

Meilleurs avis

AD

18 avr. 2021

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.

AV

5 juil. 2021

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

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1 - 25 sur 32 Avis pour Unsupervised Machine Learning

par Anish D

19 avr. 2021

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.

par Abdillah F

7 nov. 2020

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

par Hossam G M

4 oct. 2021

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.

par Ashish P

13 mars 2021

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.

par Léa Z

18 avr. 2021

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.

par az

10 mai 2022

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

par Sid C

5 avr. 2022

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.

par SMRUTI R D

20 sept. 2021

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.

par Alparslan T

6 janv. 2022

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.

par anand v

6 juil. 2021

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

par MAURICIO C

22 mai 2021

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

par george s

3 sept. 2021

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

par Marwan K

22 févr. 2022

T​hank you Coursera.

T​hank you IBM.

T​hank you to all instructors.

par Luis P S

2 juin 2021

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

par My B

23 avr. 2021

A high quality course with lots of practical techniques

par Nikolas R W

26 déc. 2020

Great course for learning about Unsupervised Learning

par Krishnendu D

11 avr. 2022

Awesome and wholesome explaination of the concepts

par Jose M

25 janv. 2021

Again, congrats to the instructor on the videos.

par Saraswati P

23 oct. 2021

W​ell structured course with many examples

par Veronica A T S

27 juin 2021

i wouuld have liked a notebook on dbscan

par Volodymyr

5 août 2021

Well balanced course, I recommend

par Wissam Z

10 oct. 2021

Very Professional course

par Uğur K

23 août 2020

Very tidy explanations

par Bernard F

26 janv. 2021

An excellent course!

par Simeon M

14 sept. 2021

Exceptional!