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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
3,380 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

JT

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Recommender Systems, Reinforcement Learning culminating in teaching a simulated Lunar Lander to land itself! I bet SpaceX something similar for the 'real' starship landing; it's much more complicated!

VB

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Great job to Andrew and crew! It would have nice to have a primer on Python and Numpy vector operations for this course. Oh well, I needed to learn Python sooner or later!

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376 - 400 of 570 Reviews for Unsupervised Learning, Recommenders, Reinforcement Learning

By ABHINAV K

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Aug 7, 2023

Best course of this series

By Joy B

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Feb 21, 2023

Excellent and informative.

By Jayesh I

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Aug 12, 2024

Great course for Learning

By Feroz K

•

Jul 17, 2024

a very informative course

By KEDUKODI B S

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Oct 25, 2022

Nicely taught! Thank you

By Maximilian S

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Sep 21, 2024

Very motivating lecturer

By Jonathan P O

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Jun 21, 2024

It´s a completely course

By Julien F

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Jul 12, 2024

Andrew, you're the best

By Cao T M Q

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May 30, 2024

This course is awesome!

By Dev C

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Apr 5, 2024

Best for the beginners

By Anuj S

•

Nov 15, 2023

most help for learning

By Schroch

•

Jul 19, 2023

Very intuitive course!

By Zakaria E J

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Jan 5, 2023

Absolutely astonishing

By PHAM C B

•

Sep 2, 2024

an awesome experience

By Chitra M G 2

•

Sep 2, 2024

encourageable classes

By Surendhran P

•

Aug 22, 2024

It is a great course.

By Chris O

•

Nov 20, 2023

beautiful and concise

By Satish P

•

Jul 27, 2023

Thank you, Andrew NG.

By V

•

Apr 7, 2023

Good level of coding.

By Arti P M

•

Sep 29, 2022

such a greate course

By Naireet S

•

Aug 20, 2024

Excellent experience

By Carlos

•

May 21, 2024

exceptional teaching

By MT H

•

Aug 25, 2023

highly rerecommended

By 邱少麒

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Jun 11, 2023

good，helpful，useful。

By abhinav r

•

Jan 10, 2023

Very well explained.