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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
32,127 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

DB

May 30, 2024

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

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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4276 - 4300 of 6,058 Reviews for Supervised Machine Learning: Regression and Classification

By Mohit N

•

Oct 24, 2025

Feeling More Confident.

By Muhammad A

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Sep 10, 2025

Nicely explained course

By teja b

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Aug 27, 2025

very useful. I loved it

By Ahmed Y A A

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Feb 28, 2025

Above my expectations!!

By Padma C

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Feb 28, 2025

Very clear explanation.

By Ram H

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Nov 12, 2024

one og the best courses

By Uttarayan H

•

Oct 28, 2024

"IN-DEPTH KNOWLEDGE" 🔥

By Federico S

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Sep 4, 2024

Complete and very clear

By Baby S

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Sep 3, 2024

Great teacher andrew Ng

By mohsin f

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Aug 26, 2024

very nice for beginners

By Youssef M

•

Aug 23, 2024

A very excellent course

By Deleted A

•

Jul 31, 2024

amazing course and lab!

By Ansari A

•

Jul 16, 2024

Love the way he teaches

By Muhammad K k

•

Jul 8, 2024

It was a great resource

By Kirellos N

•

Jul 5, 2024

Thanks a lot Mr. Andrew

By Mahmudul H

•

Jul 1, 2024

its very useful course.

By Abhishek S

•

Jun 14, 2024

How can I get the PPTs?

By Dan S

•

Feb 25, 2024

Very well formed course

By Chaithanya V

•

Feb 9, 2024

Intuitive and Inspiring

By Elizaveta K

•

Sep 27, 2023

Thanks for this course!

By Archit B

•

Aug 30, 2023

Very Nicely Explained .

By Harrison P

•

Aug 20, 2023

Very interactive course

By Nabin A

•

Aug 16, 2023

Best for ML foundations

By Hamza J

•

Jul 15, 2023

Easy to follow through.

By mohsin f

•

May 31, 2023

very nice good concepts