Chevron Left
Вернуться к Supervised Machine Learning: Classification

Отзывы учащихся о курсе Supervised Machine Learning: Classification от партнера IBM

4.9
звезд
Оценки: 74
Рецензии: 18

О курсе

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....

Лучшие рецензии

AP
28 февр. 2021 г.

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
18 янв. 2021 г.

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.

Фильтр по:

1–18 из 18 отзывов о курсе Supervised Machine Learning: Classification

автор: Paul A

6 февр. 2021 г.

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.

автор: Fitrie R

23 дек. 2020 г.

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

автор: Abdillah F

8 нояб. 2020 г.

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

автор: Ashish P

1 мар. 2021 г.

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

автор: Juan M

18 июня 2021 г.

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.

автор: Konrad B

17 дек. 2020 г.

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

автор: Jose M

19 янв. 2021 г.

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.

автор: My B

19 апр. 2021 г.

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

автор: Ranjith P

13 апр. 2021 г.

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

автор: Rorisang S

16 мая 2021 г.

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

автор: Luis P S

24 мая 2021 г.

Always a pleasure learning new ML skills through this course!

автор: Vishal J

4 дек. 2020 г.

Changed my viewpoint

автор: Nandana A

25 янв. 2021 г.

Learned a lot

автор: Pierluigi A

27 дек. 2020 г.

great

автор: MAURICIO C

17 апр. 2021 г.

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.

автор: Cristiano C

18 янв. 2021 г.

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!

автор: Keyur U

24 дек. 2020 г.

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

автор: Meith N

15 июля 2021 г.

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