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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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751 - 775 of 845 Reviews for Unsupervised Learning, Recommenders, Reinforcement Learning

By Rain L

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Nov 13, 2024

Good

By Shivanand V

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Oct 23, 2024

Nice

By Ulfah H M

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Oct 22, 2024

good

By Porco J

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Jul 3, 2024

nice

By Nguyen T N

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Apr 12, 2024

Hard

By Md. S A

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Mar 12, 2024

Best

By Naiyan N

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Mar 5, 2024

good

By Ishaan

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Jan 1, 2024

best

By HAYAA T T A

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Dec 1, 2023

روعة

By Dini P U

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Oct 19, 2023

good

By DB T

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Sep 25, 2023

Good

By RUSSO F

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Aug 23, 2023

good

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Jun 24, 2023

Good

By Wickly G

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Apr 11, 2023

good

By Angger M R

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Apr 8, 2023

good

By Ande R

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Feb 17, 2023

good

By Minakshi

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Nov 18, 2022

bhjn

By Tharun V

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Oct 31, 2022

good

By Jaber

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Sep 11, 2022

<3

By 达奇达奇上校

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Oct 24, 2025

很好

By Ritesh K S

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Nov 21, 2023

NA

By ADITYA C (

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May 8, 2023

NA

By Amitava M

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Oct 25, 2025

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By RAJ A

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Jun 15, 2025

h

By Hernán G

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Aug 31, 2023

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