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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
32,121 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.

DB

May 31, 2024

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

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4426 - 4450 of 6,057 Reviews for Supervised Machine Learning: Regression and Classification

By Alan

•

Oct 6, 2022

Very well explained!

By SABHAVATH R

•

Sep 17, 2022

i am learn new thing

By Arkan N

•

Aug 1, 2022

what a great course!

By Jitendra B

•

Dec 3, 2025

such a great course

By Alex E

•

Nov 21, 2025

Clear and enjoyable

By CFCA

•

Sep 18, 2025

Muy bueno: 9 de 10.

By André G

•

Sep 14, 2025

Great introduction!

By Chris K

•

Jul 2, 2025

Very understandable

By Kevin C

•

Apr 18, 2025

phenomenal teaching

By Elvis T

•

Mar 28, 2025

Exceptional lecture

By Odysseas K

•

Mar 12, 2025

Very undrestandable

By João P P

•

Oct 29, 2024

Absolutely amazing!

By Ahmad S

•

Oct 25, 2024

Andrew is wonderful

By Abir E E

•

Sep 16, 2024

A fantastic course!

By ali o

•

Sep 11, 2024

you're the best ang

By Progga P

•

Sep 9, 2024

It was just amazing

By Arijit P

•

Jul 31, 2024

really great course

By Abubakar K

•

Jul 25, 2024

Best for a beginner

By Venkata J B

•

Jul 25, 2024

very helpful course

By Sakthivel S

•

Jul 15, 2024

I love the content!

By yankyx

•

May 25, 2024

easy to understand!

By Soumyadip C

•

Mar 10, 2024

Great for beginners

By Thảo N

•

Feb 5, 2024

it's a great course

By Aashutosh J

•

Dec 3, 2023

Amazing explanation

By samuel 6

•

Nov 14, 2023

Hyper passionnant !