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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
32,110 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

AA

Apr 30, 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.

DB

May 31, 2024

Great intro to supervised learning (regression & classification). Clear explanation of sigmoid function and decision thresholds. Could benefit from examples & exploring non-linear boundaries.

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4551 - 4575 of 6,057 Reviews for Supervised Machine Learning: Regression and Classification

By Małgorzata G

•

Mar 26, 2023

excellent course!

By Carel T

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Mar 21, 2023

Excellent, Thanks

By henry l

•

Dec 13, 2022

wonderful course!

By 1DS21AI001 A N A

•

Nov 17, 2022

Excellent course!

By Sudip S C

•

Oct 26, 2022

Excellent course!

By Chase P

•

Oct 25, 2022

Wonderful course

By Yue C

•

Oct 20, 2022

I love the lab !

By Sonu G

•

Oct 13, 2022

Wonderful Course

By Santiago B G

•

Oct 7, 2022

Amazing teaching!

By ehsan k

•

Oct 6, 2022

Simply the best!

By GU F

•

Sep 18, 2022

nice for freshman

By Samarth C

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Aug 28, 2022

Very nice course.

By Florence P

•

Jul 10, 2022

Very well taught!

By LIKITHA C B 2

•

Jul 6, 2022

Very informative!

By Hritik A

•

Jun 30, 2022

Very Nice Content

By Fernando A

•

Jun 29, 2022

Excellent course!

By r.janani R

•

Mar 7, 2026

amazing learning

By FRANCISCO R

•

Feb 1, 2026

Curso excelente!

By Ambika S

•

Jan 17, 2026

Excellent course

By Aaradhya S

•

Dec 16, 2025

Amazing content!

By Priyansh P

•

Dec 16, 2025

very in deepth

By Md K T

•

Dec 15, 2025

Very nice module

By Mavani N

•

Nov 5, 2025

excellent cource

By Anita G M ( R - H G M

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Nov 4, 2025

Excellent course