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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
29,853 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

ED

Apr 13, 2025

Loved Andrew Ng's videos and the hands on Jupyter notebook labs! My understanding of ML has significantly improved thanks to this course and going on to the next course to complete ML specialization!!

FA

May 24, 2023

The course was extremely beginner friendly and easy to follow, loved the curriculum, learned a lot about various ML algorithms like linear, and logistic regression, and was a great overall experience.

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3551 - 3575 of 5,659 Reviews for Supervised Machine Learning: Regression and Classification

By Kishore I

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Aug 15, 2022

Excellent introductory course on ML.

By emirhan e

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Aug 7, 2022

Thanks for this precious oppurtinity.

By Carlo D

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Jul 26, 2022

best intro course to machine learning

By Anush R A

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Jul 12, 2022

best course to learn machine learning

By Daniel A

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Jul 11, 2022

Course very well executed. Thank you.

By Sayed M

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Jul 10, 2022

Thank you all for this amazing Course

By 黄金

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Jul 6, 2022

The lab part of the course is amazing

By Yuhao W

•

Jul 3, 2022

better than before, with python coded

By Gorgui B M

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Jul 1, 2022

Great professor and exellent content!

By Henrik S

•

Jun 27, 2022

It was everything I wanted it to be!

By Tanvir A F

•

Aug 14, 2025

Very helpful to understand in depth.

By Alessandro D

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Jul 20, 2025

Clear explanations, very useful Labs

By HARSH S

•

Jul 6, 2025

It was amazing ... really enjoyed it

By Aditya

•

Jun 24, 2025

it's good for being familiar with ML

By Shantanu N

•

Mar 29, 2025

Andrew Ng Sir's teaching is amazing.

By Jaswanth M

•

Feb 28, 2025

its good experiance in practice labs

By Damira A

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Feb 26, 2025

как я могу взять сертификат не могуу

By Sri K K

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Feb 16, 2025

good for basic concept understanding

By Bala A

•

Feb 15, 2025

Really like the depth of the course.

By Luke T

•

Dec 28, 2024

Beautifully explained and delivered!

By Mohammad J S

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Dec 11, 2024

perfect course I have had this year.

By Shaik M

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Jun 25, 2024

Andrew Ng is god of machine learning

By Ashirvad P

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Jun 18, 2024

Good Course ! I personally enjoy it.

By Gaurav P

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May 19, 2024

Really giving thorough understanding

By Tanuj S

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Feb 12, 2024

Great course! Thank you to Andrew Ng