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

4.9
étoiles
78 évaluations
19 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 - 19 sur 19 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 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 Konrad B

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 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 Rorisang S

16 mai 2021

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

par Luis P S

24 mai 2021

Always a pleasure learning new ML skills through this 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 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 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!

par Keyur U

24 déc. 2020

This course is has a detailed explanation on each and every aspect of classification.

par Meith N

15 juil. 2021

Need to cover some basic information and examples too cause directly start from complex examples in the code section