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Learner Reviews & Feedback for Unsupervised Learning, Recommenders, Reinforcement Learning by DeepLearning.AI

4.9
stars
3,795 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

CL

Jun 30, 2024

Good pace and really well-designed for those who are total strangers to machine learning. I could follow along quite easily and looking forward to try out some of those algorithms on my own free time.

RD

Sep 16, 2022

great introduction to machine learning. I tried to self study before but it didn't work and thanks to this course I did understand now a bunch of things I cant wrap up my head with. Thank you for this

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351 - 375 of 605 Reviews for Unsupervised Learning, Recommenders, Reinforcement Learning

By Data i n B

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Jul 8, 2023

The best machine learning program ever

By April 3

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Feb 22, 2023

Great course on reinforcement learning

By Yakov K

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May 22, 2024

Amazing quality and clarity, as usual

By Madhav M

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Sep 26, 2024

Thanks to all the team of Andrew NG.

By hoanghero 1

•

Mar 19, 2023

Easy to understand, useful knowledge

By Tajuddin M

•

Aug 18, 2022

Awesome explanation of key concepts.

By Fabio A T

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Nov 20, 2024

super Teacher and very good course.

By SONIBARE A

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Aug 23, 2024

Most educative. Thank you Coursera.

By Jihan K

•

Mar 26, 2023

informative, and easy to understand

By Reza A

•

Oct 18, 2022

It's great course. Thank you Andrew

By Srivatsav K

•

Oct 21, 2024

Good for absolute beginners in ML.

By Wilmer R V

•

Apr 19, 2024

Muy bueno, explicativo y práctico

By Sohag H (

•

Jan 8, 2024

learn a lot. love from Bangladesh

By Xuesong T

•

Jan 7, 2024

very useful course! Thank Andrew!

By Boikhutso M

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Nov 29, 2023

Very well structured intro to ML,

By Jeremy L

•

Aug 6, 2022

Amazing course!

I learned a lot!

By Abhay K

•

Sep 27, 2023

You are the best teacher so far.

By Justin H

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Mar 11, 2023

Andrew Ng. Enuff said. 👍👍👍

By Jorge A N

•

Nov 16, 2024

Exceptional course. Very clear.

By Gloria L

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May 4, 2024

I enjoyed taking this course :)

By Rolando R Z C

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Apr 25, 2024

Very carefully designed course.

By Mirro S

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Feb 23, 2024

nothing but absolutely AMAZING!

By Arjun V

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Dec 23, 2023

Learn many things, Thanks a lot

By Muhammad F R

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May 29, 2023

This course was really helpful.

By Minh D V

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Jan 19, 2023

Very informative and well-paced