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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
5,457 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

HZ

Jul 21, 2024

Got insights to what Recommender systems are and how it recommends user based on their usage and got to know how Reinforcement learning works and Successfully landed the lunar lander.

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.

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By Trisno P R

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Oct 13, 2023

josss

By Nguyễn N Q G

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Mar 10, 2023

well!

By Meryam k

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Mar 5, 2023

top !

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Sep 19, 2022

wow!

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Oct 12, 2025

best

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Aug 18, 2025

Good

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Jul 4, 2025

GOOD

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Feb 27, 2025

浅显易懂

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Nov 15, 2024

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Nov 13, 2024

Good

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Oct 23, 2024

Nice

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Oct 22, 2024

good

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Jul 3, 2024

nice

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Apr 12, 2024

Hard

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Mar 12, 2024

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Mar 5, 2024

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Jan 1, 2024

best

By HAYAA T T A

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Dec 1, 2023

روعة

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Oct 19, 2023

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Sep 24, 2023

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Aug 23, 2023

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Jun 24, 2023

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Apr 11, 2023

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Apr 8, 2023

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Feb 17, 2023

good