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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
5,420 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.

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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826 - 844 of 844 Reviews for Unsupervised Learning, Recommenders, Reinforcement Learning

By Vivek J

•

Jul 2, 2023

Best for begineers and little advance

By Kateryna K

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Mar 15, 2023

I would do more challenging labs

By Sayed A S R

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Aug 24, 2025

great intro to machine learning

By Jimmy R

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Dec 6, 2023

Great stuff, learned a lot.

By Zoe

•

Jan 7, 2025

Great for beginner.

By Haseeb A

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Aug 4, 2025

I enjoyed it a lot

By محمود ف

•

Feb 23, 2025

100% practical

By Areeba Z

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Jul 9, 2025

fantastic

By vinod t

•

Aug 26, 2022

good.

By Dhruv A

•

Aug 15, 2024

nil

By Yesid J

•

Jul 27, 2024

Mucha teoría, poca práctica.

By Sumit S

•

Nov 14, 2022

good experience

By Lior G

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Dec 28, 2024

i had a lot of problems in the grading even when i was right

By Abdulla A

•

Oct 9, 2025

Lab

By Pranav G

•

Apr 2, 2023

i didnt get to avail my certificate, though it was showing last submission date as 2nd april, i cant submit on 2nd and couldnt get my certificate

By Sanket P

•

Sep 2, 2024

I have enrolled through financial aid but it is asking me to upgrade and pay for it

By Brian

•

Jun 11, 2025

Very high level brief overview, uses out-dated TensorFlow, not practical at all.

By Vivian P

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Mar 27, 2024

Class does not exist- the links do not work

By Harsh S

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Jun 21, 2023

good course