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Volver a Unsupervised Machine Learning

Opiniones y comentarios de aprendices correspondientes a Unsupervised Machine Learning por parte de IBM

4.8
estrellas
50 calificaciones
13 reseña

Acerca del Curso

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....

Principales reseñas

AD
18 de abr. de 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.

AF
6 de nov. de 2020

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

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1 - 13 de 13 revisiones para Unsupervised Machine Learning

por Abdillah F

7 de nov. de 2020

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

por Anishkumar D

19 de abr. de 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.

por My B

23 de abr. de 2021

A high quality course with lots of practical techniques

por Nikolas R W

26 de dic. de 2020

Great course for learning about Unsupervised Learning

por Jose M

25 de ene. de 2021

Again, congrats to the instructor on the videos.

por Uğur K

23 de ago. de 2020

Very tidy explanations

por Bernard F

26 de ene. de 2021

An excellent course!

por Pierluigi A

20 de ene. de 2021

great course

por Fernandes M R

10 de mar. de 2021

very good

por Kaumil A

26 de feb. de 2021

Awesome

por Ashish P

13 de mar. de 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.

por Keyur U

24 de dic. de 2020

They have got the best instructor!

por Léa Z

18 de abr. de 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.