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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
31,768 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.

MA

Jan 28, 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.

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3926 - 3950 of 5,995 Reviews for Supervised Machine Learning: Regression and Classification

By JITENDRA K (

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Mar 20, 2024

good knowladge about this course

By Umer K

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Dec 26, 2023

Best course to satrt learning ML

By Sumaya A

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Dec 15, 2023

Excellent course for ML Beginner

By CHENGHONG L

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Dec 14, 2023

The best machine learning course

By Kishan T

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Nov 26, 2023

It is the best course! the best!

By Alexander L M

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Oct 28, 2023

Fantastic course and instructor.

By Sara N

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Sep 1, 2023

You are a good teacher Andrew Ng

By MAI A

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Aug 11, 2023

Wonderful explaining and content

By Prerana b

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Jun 13, 2023

very insightful and interesting.

By Ritik R

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Jun 8, 2023

must do course if beginner in ml

By LALIT C

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Apr 4, 2023

Intuive and Wonderful Experience

By Youcef M

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Mar 12, 2023

It is a very instructive course.

By MADDILA S A 2

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Feb 27, 2023

GOOD COURSE FOR MACHINE LEARNING

By MINHAZ C

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Feb 1, 2023

I have learned a lot! Thank you!

By Ayaz A

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Dec 29, 2022

The best ever course on internet

By Hansen C

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Dec 28, 2022

Great lecturer with great course

By Ankit K

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Dec 15, 2022

I loved the way Andrew ng taught

By Claudius M

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Nov 14, 2022

super intuitive course i love it

By Mohaned M

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Sep 11, 2022

best instructor everrrrrrrrrrrr

By Zaid R

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Jul 23, 2022

AMAZING COURSE. LOVED IT!!!!!!!!

By Diaa E

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Jul 17, 2022

i really have enjoyed the course

By Ragulkanna V

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Dec 3, 2025

Great for learning basics of ML

By Celismar O

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Sep 27, 2025

Excellent. Very well explained.

By Francesco D

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Aug 14, 2025

Outstanding Learning Experience

By Jingsheng L

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Jun 16, 2025

pretty engaging and heuristics.