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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
30,255 ratings

About the Course

In the first course of the Machine Learning Specialization, you will: 鈥� Build machine learning models in Python using popular machine learning libraries NumPy and scikit-learn. 鈥� 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鈥檚 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鈥檙e 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 14, 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!!

AD

Nov 24, 2022

Amazingly delivered course! Very impressed. The concepts are communicated very clearly and concisely, making the course content very accessible to those without a maths or computer science background.

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3926 - 3950 of 5,726 Reviews for Supervised Machine Learning: Regression and Classification

By Andres F R G

鈥�

Dec 30, 2022

Amazing introductory course!

By Alejandro A

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Nov 9, 2022

Amazing classes and teacher!

By Saravanan P

鈥�

Nov 5, 2022

Very Good!!!! Really Nice...

By Mohammad M

鈥�

Oct 11, 2022

It was perfect

Thanks Andrew

By Sudipta M

鈥�

Oct 10, 2022

Simply Amazing, Amazing !!!!

By Naresh A

鈥�

Oct 2, 2022

nice course its very useful

By Diego A S B

鈥�

Sep 9, 2022

Me enacnto el curso gracias.

By Gerd D B

鈥�

Sep 5, 2022

Awesome guys! Thanks a lot!

By Yousef E

鈥�

Aug 26, 2022

Best.

Thank you Dr.Andrew NG.

By Davide A P

鈥�

Apr 27, 2025

Very good and well teached!

By Ali E A

鈥�

Apr 20, 2025

very useful and interesting

By SUJAN M

鈥�

Apr 14, 2025

Very concise and important!

By Habibul I

鈥�

Mar 13, 2025

Great course for foundation

By Juan P L L

鈥�

Mar 9, 2025

Excelente curso y material.

By Yousif G

鈥�

Feb 17, 2025

Andrew is just phenomenal!!

By Ankit

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Feb 12, 2025

Very useful and interesting

By Feroz K

鈥�

Jan 17, 2025

fantastic, very informative

By 200_AKASH S

鈥�

Oct 1, 2024

very helpful and conceptual

By charith_neeli

鈥�

Sep 3, 2024

Excellent Work By Andrew Ng

By 膼inh N L T

鈥�

Aug 21, 2024

very good, very informative

By Mohamed H S J

鈥�

Jul 31, 2024

i love this content so much

By Akash S

鈥�

Jun 17, 2024

Very good and informational

By Nishanth R

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Mar 24, 2024

very useful and interactive

By Koyyada D

鈥�

Mar 13, 2024

Andrew sir you are awesome.

By Chikkala L N

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Feb 4, 2024

excellent math involve ment