This course introduces you to one of the main types of modelling families of supervised Machine Learning: Regression. You will learn how to train regression models to predict continuous outcomes and how to use error metrics to compare across different models. This course also walks you through best practices, including train and test splits, and regularization techniques.
About this Course
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.
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TOP REVIEWS FROM SUPERVISED MACHINE LEARNING: REGRESSION
Very well designed course, great that we could work with our own data and apply the theory. Looking forward to continue the journey.
Great course and very well structured. I'm really impressed with the instructor who give thorough walkthrough to the code.
Learned really about supervised learning and more importantly regularization and some available methods.
I recommend this course to everyone who wants to excel in Machine Learning. This is a Great Course!
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