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Back to Supervised Machine Learning: Regression and Classification

Learner Reviews & Feedback for Supervised Machine Learning: Regression and Classification by DeepLearning.AI

4.9
stars
32,099 ratings

About the Course

In the first course of the Machine Learning Specialization, you will: • Build machine learning models in Python using popular machine learning libraries NumPy and scikit-learn. • Build and train supervised machine learning models for prediction and binary classification tasks, including linear regression and logistic regression The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. In this beginner-friendly program, you will learn the fundamentals of machine learning and how to use these techniques to build real-world AI applications. This Specialization is taught by Andrew Ng, an AI visionary who has led critical research at Stanford University and groundbreaking work at Google Brain, Baidu, and Landing.AI to advance the AI field. This 3-course Specialization is an updated and expanded version of Andrew’s pioneering Machine Learning course, rated 4.9 out of 5 and taken by over 4.8 million learners since it launched in 2012. It provides a broad introduction to modern machine learning, including supervised learning (multiple linear regression, logistic regression, neural networks, and decision trees), unsupervised learning (clustering, dimensionality reduction, recommender systems), and some of the best practices used in Silicon Valley for artificial intelligence and machine learning innovation (evaluating and tuning models, taking a data-centric approach to improving performance, and more.) By the end of this Specialization, you will have mastered key concepts and gained the practical know-how to quickly and powerfully apply machine learning to challenging real-world problems. If you’re looking to break into AI or build a career in machine learning, the new Machine Learning Specialization is the best place to start....

Top reviews

YD

Oct 2, 2022

E​xcellent course. Intended as a refresher, and had a better understanding of feauture engineering, scaling, and logistic regression. Good hands on labs were very practical, engaging and rewarding.

AA

Apr 29, 2023

Optional Lab lot more time than mentioned without prior experience of python and libraries used. Its estimated time should be change, it's a lot more than 1 hour. Video and exercises are very good.

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4251 - 4275 of 6,055 Reviews for Supervised Machine Learning: Regression and Classification

By Michal G

•

Nov 7, 2023

Very good course. Thanks

By Omar A

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Oct 27, 2023

very goooooooooooooooood

By Mohammed A

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Oct 14, 2023

This course was superb!!

By Mirko J

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Oct 6, 2023

Great code practices ...

By Farshad H

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Sep 30, 2023

That was really awesome.

By Hossam A A

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Jun 25, 2023

very useful introduction

By mahan k

•

Jun 19, 2023

best introduction course

By Jeremiah

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May 20, 2023

Really fantastic course!

By Azim S E

•

May 1, 2023

this is wonderful course

By Julian m

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Apr 10, 2023

Brilliant, great course.

By Kailashpati M S

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Mar 22, 2023

Amazing experience .....

By Heizly S

•

Jan 12, 2023

Muy buenas explicaciones

By Alessandro P

•

Dec 26, 2022

It is an amazing course!

By Lizhi Z

•

Nov 26, 2022

Excellent and Ingenious

By Gu B

•

Aug 25, 2022

pretty good. Recommended

By shagufta p

•

Aug 24, 2022

It was very informative

By Niskarsh D

•

Aug 20, 2022

Course was pretty nice !

By Sandarbh S

•

Aug 17, 2022

Excellent Experience!!!1

By Sobhan A

•

Jul 31, 2022

Thanks for supporting us

By Fatma A e

•

Jul 22, 2022

great content thank you

By Ninoslav C

•

Jul 6, 2022

This course is brillant!

By Tom J

•

Jun 25, 2022

Top notch. Superlative.

By Matias M

•

Feb 14, 2026

Very clear explanations

By Mohit N

•

Oct 24, 2025

Feeling More Confident.

By Muhammad A

•

Sep 10, 2025

Nicely explained course