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Back to Unsupervised Learning, Recommenders, Reinforcement Learning

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

4.9
stars
5,251 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

ML

Dec 12, 2022

The whole specialisation is a great quick review of main topics. Proper learning requires deeper knowledge of algebra, calculus and python. But these courses are a fast, essential starting point.

AM

Mar 10, 2024

This course has offered invaluable insights and clarity in understanding machine learning concepts. It was a nice journey towards understanding practical application and complex concepts made easy.

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501 - 525 of 810 Reviews for Unsupervised Learning, Recommenders, Reinforcement Learning

By Rishi D

•

Nov 23, 2022

Thank you Prof Andrew & team!!

By Ankit P

•

Aug 28, 2022

This course is just fantastic.

By Sewasew T

•

Feb 1, 2025

i just want to say THANK YOU!

By AKULA P R

•

Oct 22, 2024

very good learning experience

By Crhis

•

Jul 17, 2024

This is just perfect teaching

By Ali A

•

Jan 26, 2024

Best course i ever take in ML

By David R

•

Oct 7, 2023

Andrew is a wonderful teacher

By abdelrahman a

•

Sep 6, 2023

Thanks a lot for your efforts

By Huajie C

•

Feb 13, 2023

Great course, love Andrew Ng.

By Saatwik U

•

Aug 16, 2025

Nice and good for beginners.

By Yongli L

•

Jan 4, 2024

Absolutely love this course.

By Harsh J

•

Oct 18, 2023

best ml course in the market

By Tanu J

•

Oct 11, 2023

Specific, simple and through

By Ananda B

•

Jul 3, 2023

A lot of new topics to cover

By Peter R

•

Sep 26, 2022

I learnt so much thank you.

By Shah F M

•

Aug 21, 2025

best professor , Andrew sir

By Francesco D

•

Aug 18, 2025

Great Learning Experience !

By NarasimhaMurthy V

•

Oct 15, 2025

Great course for beginners

By Priyam G

•

Aug 11, 2025

Crazyy good learnt so much

By nithya v

•

Aug 17, 2024

Excellent course material.

By Dietmar M

•

Jul 2, 2024

Exiting course, sparks joy

By AARYAV D (

•

Sep 9, 2023

It was a very good course.

By ABHINAV K

•

Aug 7, 2023

Best course of this series

By Joy B

•

Feb 21, 2023

Excellent and informative.

By liguo z

•

Oct 8, 2025

This course is well worth