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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
30,502 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

MA

Jan 27, 2025

I've really enjoyed learning about Machine Learning in such a guided way. It will continue to inspire me to learn more about AI. Thank you Andrew Ng, DeepLearning.AI, Standford ONLINE, and Coursera.

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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3751 - 3775 of 5,778 Reviews for Supervised Machine Learning: Regression and Classification

By Oleksii K

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Aug 30, 2022

The best introductory course ever.

By Rahul k

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Oct 7, 2025

this course is so helpful for me.

By David T

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Jul 3, 2025

A masterclass in Machine Learning

By Sijan T M

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Mar 23, 2025

Its best course i have ever taken

By Shivabhijit S

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Mar 16, 2025

Topics were explained Really well

By Prakash

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Mar 9, 2025

Everything is explained clearly!!

By Kifayatullah

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Feb 5, 2025

One of the Most important Subject

By RL

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Dec 3, 2024

Learned about a lot of new things

By Hamdan K

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Nov 24, 2024

A great learning resource for ML.

By BONAM R

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Oct 1, 2024

Best Course for Machine Learning.

By harshit r

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Jul 30, 2024

very helpful course for begineers

By Haitam B

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Jul 29, 2024

thank you for this amazing course

By Ishaan J

•

May 10, 2024

Epic course By the GOAT Andrew NG

By Eranda J

•

Apr 23, 2024

Great course. Highly recommended.

By ANINDYA M

•

Jan 24, 2024

A great course to kick off the ML

By Quynh A N

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Dec 22, 2023

Great course, easy to understand!

By Lung C H

•

Nov 29, 2023

easy to understand all the things

By Jin

•

Nov 3, 2023

Great learning materials! Thanks!

By Vishal K G

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Oct 14, 2023

loved it.. very nice explanation.

By Fahrul A N

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Oct 5, 2023

Andrew Ng is the best instructor!

By Mohit K

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Sep 13, 2023

The Way of explaining is too good

By Tiong W

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Aug 26, 2023

help to build my basics stronger.

By Everton D

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Aug 15, 2023

Difficult but excellent course!!!

By Muttakin K

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Aug 12, 2023

A very good course for begineers.

By Emin A

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Jul 29, 2023

very entertaining and educational