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Learner Reviews & Feedback for Supervised Machine Learning: Regression by IBM

4.7
stars
805 ratings

About the Course

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. By the end of this course you should be able to: Differentiate uses and applications of classification and regression in the context of supervised machine learning聽 Describe and use linear regression models Use a variety of error metrics to compare and select a linear regression model that best suits your data Articulate why regularization may help prevent overfitting Use regularization regressions: Ridge, LASSO, and Elastic net 聽 Who should take this course? This course targets aspiring data scientists interested in acquiring hands-on experience聽 with Supervised Machine Learning Regression techniques in a business setting. 聽 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....

Top reviews

VO

Apr 10, 2021

Very well presented. This is without doubt the best series for Machine Learning on 糖心vlog官网观看.

AK

Jul 2, 2023

Highly recommended if you want to learn Supervised learning : regression professionally with library. You should have prior knowledge to mathematics.

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151 - 152 of 152 Reviews for Supervised Machine Learning: Regression

By Rick B

鈥�

May 22, 2025

This would be a fantastic course, but there are no handouts! First off It would be nice to have a notebook on the code you're working on, since trying to follow along squinting at the instructor's notebook, is very poor way of teaching. You spend most of the lecture writing notes, so you may miss something the instructor says. You have better classes on the subject such as the University of Michigan's class. This class was the breaking point with IBM, especially as you get into the more technical issues. I appreciate IBM putting the material out but I have had it.

By mxio

鈥�

Jul 3, 2025

Too many Quizzes graded incorrectly