Chevron Left
Supervised Machine Learning: Classification に戻る

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

4.8
171件の評価

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

NR

2022年2月21日

Great course, well structured. The presentation of the different methods is very clear and well separated to understand the differences. A good understanding of classifiers is gained from this course.

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!

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

フィルター:

Supervised Machine Learning: Classification: 1 - 25 / 44 レビュー

by Paul A

2021年2月6日

by Fitrie R

2020年12月23日

by Ashish P

2021年3月1日

by Abdillah F

2020年11月8日

by Volodymyr

2021年7月28日

by Hossam G M

2021年8月22日

by SMRUTI R D

2021年8月27日

by Pulkit K

2021年10月1日

by Nicola R

2022年2月22日

by Juan M

2021年6月18日

by Alparslan T

2022年1月7日

by Vallian S

2022年8月8日

by konutek

2020年12月17日

by Jose M

2021年1月19日

by nico l

2021年11月26日

by Saraswati P

2021年9月23日

by JV K

2022年9月15日

by My B

2021年4月19日

by Ranjith P

2021年4月13日

by Hariom S

2021年10月2日

by Rorisang S

2021年5月16日

by Paulo E B d M

2022年6月8日

by Kevin P

2022年3月21日

by george s

2021年8月30日

by Marwan K

2021年11月23日