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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

Apr 10, 2021

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

Feb 24, 2022

AN amazing course and contain really time values content only regret is that coursera doesn't come in dark mode

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76 - 100 of 152 Reviews for Supervised Machine Learning: Regression

By Malligesh

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Oct 21, 2024

great course

By ALI S

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Oct 5, 2024

Great course

By Meghashree A

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Sep 26, 2024

very helpful

By Federico C

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Oct 6, 2023

Great course

By Shatha J

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Mar 11, 2025

good coerce

By Marcelo R c

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Jul 17, 2023

Loved it :)

By Victor M C

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Jul 28, 2024

buen curso

By Vandhan M K

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Jul 31, 2022

I loved it

By Cui Y

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Jan 15, 2022

Thank you!

By Rorisang S

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May 4, 2021

Excellent!

By Giovanny A J T

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Mar 4, 2025

Excelente

By Janier R

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Mar 5, 2024

thank you

By Varun S

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Dec 26, 2022

Excellent

By Takahide M

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Jul 14, 2022

amazing.

By Abdur R K

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Sep 16, 2021

excellent

By Sangita B

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Jul 20, 2025

Amazing

By Sevinchbonu K

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Mar 28, 2025

AJOYIB

By Hariom K

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Jan 23, 2022

Thanks

By Deb K

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Apr 21, 2025

coool

By Tahani L

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Nov 9, 2024

噩賲賷賱丞

By Guru P N

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Sep 24, 2022

Good

By Saeid S S

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Apr 13, 2022

great

By Volodymyr

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Jul 15, 2021

Super

By ADRI M

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Oct 9, 2025

good

By Rahul C

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Aug 16, 2025

good