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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
31,490 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.

WB

May 24, 2024

amazing course and super easy to follow. my only problem is that it doesn't delve too deeply into the math and science of things and focuses more on practical applications rather than how things work

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5751 - 5775 of 5,958 Reviews for Supervised Machine Learning: Regression and Classification

By Ajay C

•

Sep 21, 2024

Very useful to my career development

By geet c

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Mar 31, 2023

Really Good Course to start of with

By Kunal E 2 P U

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Aug 21, 2022

The labwork can be much much better

By Kritagyay U

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Aug 28, 2023

The course structure is awesome .

By Abhishek K

•

Aug 12, 2023

Optional part should be explained

By Amirhossein N

•

May 27, 2023

thanks to Andrew NG. It was well.

By 20ECE053 M A I

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Sep 24, 2022

Really interesting, Good teacher

By shubhankar

•

Nov 14, 2025

good for fundaments and concepts

By M B K

•

Oct 13, 2025

very deeply and nicely explained

By Ishit A

•

Aug 21, 2023

great explanation for beginners.

By L. M

•

Nov 8, 2025

difficult but very informative.

By Mohit Y

•

Jun 9, 2023

I expected more rigrous course.

By WONG, L H K

•

May 23, 2023

No enough mathematical concepts

By Ameya S

•

Aug 24, 2024

Nicely explained for beginners

By Kartik

•

Sep 28, 2025

Needed more questions in quiz

By SS K

•

Jun 21, 2025

i like the way of teaching

By M F R

•

Aug 29, 2022

Very well organized course.

By raj t

•

Oct 7, 2024

very helpful for begginers

By Zeyad M A

•

Jul 23, 2024

Lacks end-to-end projects

By Ritil R

•

Jul 6, 2023

teach in a very basic way

By F S

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Jul 1, 2023

need more code assignment

By Manish P

•

Oct 30, 2025

Good indepth into basics

By Safwen S

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Jul 29, 2024

lacks practical examples