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Supervised Learning: Classification に戻る

IBM による Supervised Learning: Classification の受講者のレビューおよびフィードバック

4.9
42件の評価
11件のレビュー

コースについて

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....

人気のレビュー

AP
2021年2月28日

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
2021年1月18日

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.

フィルター:

Supervised Learning: Classification: 1 - 11 / 11 レビュー

by Fitrie R

2020年12月23日

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

by Paul A

2021年2月6日

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.

by Ashish P

2021年3月1日

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

by Konrad B

2020年12月17日

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

by Jose M

2021年1月19日

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.

by Abdillah F

2020年11月8日

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

by Vishal J

2020年12月4日

Changed my viewpoint

by Nandana A

2021年1月25日

Learned a lot

by Pierluigi A

2020年12月27日

great

by Cristiano C

2021年1月18日

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!

by Keyur U

2020年12月24日

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