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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
5,421 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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701 - 725 of 846 Reviews for Unsupervised Learning, Recommenders, Reinforcement Learning

By Thilak t

•

Jul 24, 2024

excellent

By João V

•

May 3, 2024

THE GOAT!

By raid a B

•

Mar 30, 2024

Andrew <3

By Carlos M M M

•

Feb 15, 2024

Brilliant

By Akansha y

•

Oct 18, 2023

Excellent

By Albert H

•

Oct 3, 2023

Excellent

By Muhammad T H

•

Sep 26, 2023

Very Nice

By Prithwijit G

•

Jun 14, 2023

Excellent

By Data I M

•

Apr 5, 2023

very like

By yugdeep p

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Mar 16, 2023

very good

By parade

•

Dec 21, 2022

wonderful

By Swastik R

•

Jan 8, 2026

Yee-Haw!

By Nam A S Đ T

•

Apr 2, 2025

nice one

By Prachet P

•

Sep 21, 2024

Worthy!!

By Achyuth S

•

Aug 2, 2023

Awesome.

By Navin D

•

Oct 22, 2022

perfect

By Gelli V S G

•

Oct 9, 2022

Awesome

By 하재현

•

Sep 3, 2022

perfect

By Ramkumar

•

Aug 19, 2022

the best

By shijie j

•

Jul 12, 2025

非常棒的课程！

By mfl828

•

Apr 13, 2025

awesome

By Khaled Z

•

Apr 5, 2025

perfect

By YACINE

•

Jan 21, 2025

love it

By Yanuar Z

•

Dec 29, 2024

Awesome

By Onur C C

•

Oct 25, 2024

amazıng