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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
27,853 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 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!!

FA

May 25, 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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3851 - 3875 of 5,338 Reviews for Supervised Machine Learning: Regression and Classification

By Nabin A

•

Aug 16, 2023

Best for ML foundations

By Hamza J

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Jul 15, 2023

Easy to follow through.

By mohsin f

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May 31, 2023

very nice good concepts

By Sundaresan S

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May 19, 2023

nice and more intuitive

By Arpit S

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May 10, 2023

very informative course

By Amresh G

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Apr 16, 2023

very good for beginners

By RUIZE X

•

Feb 18, 2023

very easy to understand

By Mohamed M

•

Feb 3, 2023

the course is so great.

By Trần T A

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Jan 30, 2023

Easily understandable !

By Om p

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Jan 1, 2023

nice and knowledgeable.

By Rahul D

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Dec 2, 2022

In one word , Amazing !

By Junaid T

•

Oct 23, 2022

Excellent Course !!!!

By Anwesha C

•

Oct 6, 2022

Excellent explanation.

By 邓明

•

Sep 16, 2022

Best ML course so far.

By 20131A4441 N Y V N S

•

Aug 16, 2022

very good for beginners

By SOURAV D

•

Aug 10, 2022

Awesome Course to learn

By Walid s

•

Aug 6, 2022

good method in teaching

By Saikrishna M

•

Jul 31, 2022

Very nice experience .

By Preshit T

•

Mar 7, 2025

Best course out there!

By Punith K K

•

Feb 1, 2025

Great learning content

By JinSoo K

•

Jan 3, 2025

It was a great course!

By Dhruv G

•

Nov 2, 2024

very helpful and basic

By Karen O

•

Oct 15, 2024

¡Excellent, thank you!

By Tuyen T

•

Sep 12, 2024

Very interested course

By Laura M C

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Aug 27, 2024

Te da muy buenas bases