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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
30,219 ratings

About the Course

In the first course of the Machine Learning Specialization, you will: 鈥� Build machine learning models in Python using popular machine learning libraries NumPy and scikit-learn. 鈥� 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鈥檚 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鈥檙e 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

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.

AD

Nov 24, 2022

Amazingly delivered course! Very impressed. The concepts are communicated very clearly and concisely, making the course content very accessible to those without a maths or computer science background.

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5426 - 5450 of 5,721 Reviews for Supervised Machine Learning: Regression and Classification

By Ehsan H

鈥�

Mar 22, 2025

It could be better if we were more engaged in coding and performing tasks on datasets.

By Purva T

鈥�

Nov 30, 2023

Andrew Ng has explained every topic in depth and all lectures are easy to understand.

By SREEHARSH N

鈥�

Jun 12, 2023

Great course for those who are looking to step into the world of machine learning!!!

By Rameshbabu

鈥�

May 9, 2023

Great Training. Suggest to add one additional lectures to brush up the mathematics.

By Shashank A

鈥�

Sep 13, 2024

The last portion(logistic regression) looks a bit rushed than the linear regression

By Pelumi A

鈥�

Jun 28, 2025

Good course for foundations and theoretical aspects, not much for practical though

By Ikhlaq A

鈥�

Feb 5, 2025

very deep and understandable lectures notes and labs, overall course is excellent

By Eman M

鈥�

Sep 23, 2023

Your lab session has timed out If you'd like to continue working, reopen the lab.

By Deleted A

鈥�

Nov 29, 2022

There is no actual way to learn the basics of Python, you just CTRL+F other labs.

By 氅旐儉氩勳姢韥Μ鞐愳澊韯�

鈥�

Mar 30, 2023

觳橃潓鞐愲姅 臁瓣笀 鞏措牭瓿� 氕愱皜 氕旍 氇半瀽歆�毵� 鞝愳爯 鞚奠垯頃挫旮� 鞁滌瀾頄堨姷雼堧嫟.. 鞎烄溂搿� 鞛愳＜ 氚╇頃挫劀 雿� AI鞐� 雽�頃� 雿� 毵庫潃 鞝曤炒毳� 鞏浑弰搿� 頃橁矤鞀惦媹雼�

By Daniel N

鈥�

Jul 12, 2022

Interesting, and useful, take on how the different topics relate to each other.

By Joshua E

鈥�

Jun 13, 2023

The math can be confusing if you want to understand why the code is what it is.

By LALIT K

鈥�

Oct 24, 2022

it was nice ,and with full touch of practical knowledge,it was really helpfull

By Sohrab M

鈥�

Aug 29, 2022

I am really appreciated for being part of this community and learn new skills.

By ABHISHEK A

鈥�

Jul 25, 2022

Great course but I wish instructor also explaned the option lap code as well.

By Gustavo T

鈥�

Jul 22, 2022

Great content and learning pace. Just think the assignements could be harder.

By Shreejay M

鈥�

Feb 27, 2025

Excellent Course. A very specific and detailed path is taken by this course.

By Mohd A A

鈥�

Jan 25, 2025

Optional Labs would have been Interesting Only if they were not optional :-)

By mohammad m m

鈥�

Jan 27, 2023

perfect, but mathematics and academics subject was lesser than it should be

By Fahad A

鈥�

Jan 30, 2024

Overall the course is good but you should upgrade your labs;they are worse

By Thomas G

鈥�

Feb 25, 2023

The programming style in the labs is much more complicated than necessary.

By Arindam P

鈥�

May 31, 2024

Very well structured , well drafted and good difficulty level assignments

By Yashu A

鈥�

Jun 21, 2023

it was an amazing course overall but I expected more mathematical details

By Magdy E

鈥�

Feb 9, 2023

It's a good first step in Machine Learning and this course was so helpful

By Suvroneel N

鈥�

Jan 8, 2024

labs were helpful but could've been better to explain the codes in video