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.
이 강좌에 대하여
귀하가 습득할 기술
IBM is the global leader in business transformation through an open hybrid cloud platform and AI, serving clients in more than 170 countries around the world. Today 47 of the Fortune 50 Companies rely on the IBM Cloud to run their business, and IBM Watson enterprise AI is hard at work in more than 30,000 engagements. IBM is also one of the world’s most vital corporate research organizations, with 28 consecutive years of patent leadership. Above all, guided by principles for trust and transparency and support for a more inclusive society, IBM is committed to being a responsible technology innovator and a force for good in the world.
- 5 stars88.46%
- 4 stars10.89%
- 3 stars0.64%
SUPERVISED MACHINE LEARNING: CLASSIFICATION의 최상위 리뷰
Great course and very well structured. I'm really impressed with the instructor who give thorough walkthrough to the code.
I recommend this course to everyone who wants to excel in Machine Learning. This is a Great Course!
A well-structured and practical course which helps me answer lots of my concerns from the past until now.
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.