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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
5,423 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

HA

Sep 25, 2022

T​he content was details, explained thoroughly and understandable. But, when it came to implementation, few more labs similar to the structure of previous course could have improved it more.

TF

Jul 17, 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.

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726 - 750 of 846 Reviews for Unsupervised Learning, Recommenders, Reinforcement Learning

By Deni K

•

Oct 11, 2024

amazing

By Ifeanyi A

•

Aug 31, 2024

Amazing

By Hesam A

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Jul 8, 2024

perfect

By Fausto R

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Jun 22, 2024

Ta weno

By Muhammad K I

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Apr 15, 2024

awesome

By Saffanah N F

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Apr 13, 2024

amazing

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Feb 28, 2024

Awesome

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Jan 15, 2024

awesome

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Mar 23, 2025

Thanks

By Ferry A

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Oct 23, 2024

greatt

By Huỳnh T T

•

Jul 26, 2023

Great!

By 刘楚墙

•

Mar 31, 2023

useful

By seyed m s m

•

Dec 15, 2022

THANKS

By M O

•

Dec 4, 2022

great!

By Alfred A

•

Oct 30, 2025

Super

By Mete U

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Mar 18, 2025

GREAT

By Mukhammad I K

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Oct 23, 2024

great

By Trisno P R

•

Oct 13, 2023

josss

By Nguyễn N Q G

•

Mar 10, 2023

well!

By Meryam k

•

Mar 5, 2023

top !

By Birhanu G

•

Sep 19, 2022

wow!

By Jabez S

•

Oct 12, 2025

best

By Sujair I

•

Aug 18, 2025

Good

By FEDI H

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Jul 4, 2025

GOOD

By Gene K

•

Feb 27, 2025

浅显易懂