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Avis et commentaires pour d'étudiants pour Supervised Machine Learning: Classification par IBM

4.9
étoiles
102 évaluations
26 avis

À propos du cours

This course introduces you to one of the main types of modeling families of supervised Machine Learning: Classification. You will learn how to train predictive models to classify categorical outcomes and how to use error metrics to compare across different models. The hands-on section of this course focuses on using best practices for classification, including train and test splits, and handling data sets with unbalanced classes. By the end of this course you should be able to: -Differentiate uses and applications of classification and classification ensembles -Describe and use logistic regression models -Describe and use decision tree and tree-ensemble models -Describe and use other ensemble methods for classification -Use a variety of error metrics to compare and select the classification model that best suits your data -Use oversampling and undersampling as techniques to handle unbalanced classes in a data set   Who should take this course? This course targets aspiring data scientists interested in acquiring hands-on experience with Supervised Machine Learning Classification 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

AP
28 févr. 2021

Superb ,detailed, well explained, lots of hands on training through labs and most of the major alogrithms are covered!\n\nKeep up the good work. You guys are helping the community a lot :D

JM
17 juin 2021

The course is very well structured, and the explanations very clear. I would only suggest enhancing the peer-review community since it takes a long time to get a review sometimes.

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1 - 25 sur 27 Avis pour Supervised Machine Learning: Classification

par Paul A

6 févr. 2021

Overall, an excellent course. It gives a great introduction to many of modern and old machine learning models, and a brief glimpse in dealing with unbalanced data; a subject you can freely explore on your own. The strongest part of this course are the guided demos, they are excellent to see things happen in real time, with many ah-ha! moments, and filled code you can adapt to other projects.

However, there's a catch; to me, a big one. The guided demos; although excellent, are flawed. If you follow the practices presented in the demo, you generate a lot of data leakage into the predictions. Specially when doing cross validation with gridsearch, since the training is not done with a pipeline. Be careful when implementing your own machine learning models after following this course.

par Fitrie R

23 déc. 2020

This course is a next level after understanding classification machine learning model. All my questions had been answered with this module. The instructor is very great to clarify the whole python code used. Highly recommended course

par Ashish P

1 mars 2021

Superb ,detailed, well explained, lots of hands on training through labs and most of the major alogrithms are covered!

Keep up the good work. You guys are helping the community a lot :D

par Abdillah F

8 nov. 2020

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

par Volodymyr

28 juil. 2021

Very good material and approach to Human Learning +5 :)

par SMRUTI R D

27 août 2021

It is an excellent course on Classification. The approach of the course is different from similar courses I had attended earlier. It presents different classification algorithms as a continuous whole with increasing degree of sophistication rather as disjoint ones. This helped in understanding the entire range of available options and how to apply them in different situations. The faculty was very clear and precise in his presentations. Many thanks to IBM / Coursera.

par Pulkit K

1 oct. 2021

E​xcellent course . I have done a lot of data science courses on Coursera and this one by far is the most comprehensive course on this subject matter and the training examples in the notebook, all are very well explained. Highly recommend it to everyone.

par Juan M

18 juin 2021

The course is very well structured, and the explanations very clear. I would only suggest enhancing the peer-review community since it takes a long time to get a review sometimes.

par konutech

17 déc. 2020

The instructor from videos is amazing. Great tutor. So far the courses from IBM Machine Learning Professional Certificate are really, really good.

par Jose M

19 janv. 2021

I would like to give especial thanks to the instructor (the one in the videos) for his great job. It would be nice to know who is is.

par Saraswati P

23 sept. 2021

Well structured training. Lab sessions and assignments are well planned to get clarity on concepts and practical application.

par My B

19 avr. 2021

A well-structured and practical course which helps me answer lots of my concerns from the past until now.

par Ranjith P

13 avr. 2021

I recommend this course to everyone who wants to excel in Machine Learning. This is a Great Course!

par Hariom S

2 oct. 2021

It was a perfect experience and the instructor was very good. Thanks, IMB and Coursera

par Rorisang S

16 mai 2021

Fantastic presentations and detailed course material make this course really worth it!

par george s

30 août 2021

One of the best courses offered by IBM and coursera, 100% recommended.

par Luis P S

24 mai 2021

Always a pleasure learning new ML skills through this course!

par Wissam Z

22 août 2021

Best professional machine learning course

par Vishal J

4 déc. 2020

Changed my viewpoint

par Nandana A

25 janv. 2021

Learned a lot

par Pierluigi A

27 déc. 2020

great

par Rohit P

16 oct. 2021

Best

par MAURICIO C

17 avr. 2021

there is a lot of information with machine learning strategies and explain how to think in front of results. Super Course ! JSON files made me confusion, it mentions notebook jupiter files but not.

par Hossam G M

22 août 2021

The course content is very great in the coding area and it is very helping. but a shortage that is clear is the theory behind every algorithm, the handling of it wasn't that much perfect.

par Cristiano C

18 janv. 2021

Interesting Course, sometimes it skips some arguments that should be, imho, studied a bit deeper (i.e. UP/DOWN sampling), for the rest it's a great course with a great teacher!