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Learner Reviews & Feedback for Unsupervised Learning, Recommenders, Reinforcement Learning by DeepLearning.AI

4.9
stars
5,434 ratings

About the Course

In the third course of the Machine Learning Specialization, you will: • Use unsupervised learning techniques for unsupervised learning: including clustering and anomaly detection. • Build recommender systems with a collaborative filtering approach and a content-based deep learning method. • Build a deep reinforcement learning model. 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

TF

Jul 18, 2023

I hope more and more engineers in Japan take this course.The joy of learning machine learning with the world's top lecturer far outweighs the pain learning the subject in the non-native language.

TK

Sep 10, 2022

I​t simply exceeded my expectations. I recommend it to whoever who is trying to learn the concepts and need tips related to industry practices, and overall wants an applied approach.

Filter by:

501 - 525 of 853 Reviews for Unsupervised Learning, Recommenders, Reinforcement Learning

By srivatsav k

•

Oct 21, 2024

Good for absolute beginners in ML.

By Amos P

•

Jan 11, 2025

Well structured and easy to learn

By Wilmer R V

•

Apr 20, 2024

Muy bueno, explicativo y práctico

By Sohag H (

•

Jan 9, 2024

learn a lot. love from Bangladesh

By Xuesong T

•

Jan 7, 2024

very useful course! Thank Andrew!

By Boikhutso M

•

Nov 29, 2023

Very well structured intro to ML,

By Jeremy L

•

Aug 6, 2022

Amazing course!

I learned a lot!

By Jeremy S

•

Oct 17, 2025

Andrew is an incredible teacher!

By Nguyễn N M

•

Sep 18, 2025

a very good course for beginners

By Sikiru Y

•

Jun 7, 2025

I found it profoundly impactful.

By Mathivathani S

•

Apr 25, 2025

Excellent course, Thanks Andrew!

By Jalal U D B

•

Jan 22, 2025

best course for machine learning

By Abhay K

•

Sep 28, 2023

You are the best teacher so far.

By Justin H

•

Mar 11, 2023

Andrew Ng. Enuff said. 👍👍👍

By Joshua M

•

May 30, 2025

Great Course. Sign up. Learn.

By Jorge A N

•

Nov 16, 2024

Exceptional course. Very clear.

By G L

•

May 5, 2024

I enjoyed taking this course :)

By Rolando R Z C

•

Apr 26, 2024

Very carefully designed course.

By Mirro S

•

Feb 23, 2024

nothing but absolutely AMAZING!

By Arjun V

•

Dec 23, 2023

Learn many things, Thanks a lot

By Muhammad F R

•

May 30, 2023

This course was really helpful.

By Minh D V

•

Jan 20, 2023

Very informative and well-paced

By nicolas b

•

Jan 21, 2026

solid course. Very recommended

By Mati V

•

Nov 4, 2024

Nothing more than exceptional!

By Subodha G

•

Nov 26, 2023

Highly recommend for beginners