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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
3,960 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

Jun 7, 2024

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!

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.

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526 - 550 of 630 Reviews for Unsupervised Learning, Recommenders, Reinforcement Learning

By Akansha y

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Oct 18, 2023

Excellent

By Albert H

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Oct 3, 2023

Excellent

By Muhammad T H

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Sep 26, 2023

Very Nice

By Prithwijit G

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Jun 14, 2023

Excellent

By Data I M

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Apr 5, 2023

very like

By yugdeep p

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Mar 16, 2023

very good

By parade

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Dec 21, 2022

wonderful

By Prachet P

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Sep 21, 2024

Worthy!!

By Achyuth S

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Aug 2, 2023

Awesome.

By Navin D

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Oct 22, 2022

perfect

By Gelli V S G

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Oct 9, 2022

Awesome

By 하재현

•

Sep 3, 2022

perfect

By Ramkumar

•

Aug 19, 2022

the best

By Yanuar Z

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Dec 29, 2024

Awesome

By Onur C C

•

Oct 25, 2024

amazıng

By Deni K

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Oct 11, 2024

amazing

By Ifeanyi A

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Aug 31, 2024

Amazing

By Hesam A

•

Jul 8, 2024

perfect

By Fausto R

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Jun 22, 2024

Ta weno

By Muhammad K I

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Apr 15, 2024

awesome

By Saffanah N F

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Apr 13, 2024

amazing

By Idir b

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Feb 28, 2024

Awesome

By Sakshi P

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Jan 15, 2024

awesome

By Ferry A

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Oct 23, 2024

greatt

By Huỳnh T T

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Jul 26, 2023

Great!