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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
4,102 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.

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!

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626 - 646 of 646 Reviews for Unsupervised Learning, Recommenders, Reinforcement Learning

By Mayank D

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Dec 10, 2023

the practice assignments were very disturbing and took lot of time

By Wassim R

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May 31, 2023

Thank you.

I suggest adding more optional labs before practie labs.

By KUSUMLATA K

•

Nov 24, 2024

The assignment are very useful and informative, thanks alot.

By vaibhav v

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Mar 30, 2024

I think the exercises could be a bit more challenging

By Nathan H

•

Oct 16, 2023

great foundational course with the fundamental math

By Manu C

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Nov 19, 2024

Me gustaría que hubiera mas ejercicios prácticos.

By Vasanthan B

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Aug 20, 2024

Excellent curriculum for AI/ML beginners.

By Abhinav P

•

Jan 7, 2024

wish it were more implementation focused

By Vivek J

•

Jul 2, 2023

Best for begineers and little advance

By Kateryna K

•

Mar 15, 2023

I would do more challenging labs

By Jimmy R

•

Dec 6, 2023

Great stuff, learned a lot.

By Zoe

•

Jan 7, 2025

Great for beginner.

By vinod t

•

Aug 26, 2022

good.

By Dhruv A

•

Aug 15, 2024

nil

By Yesid J

•

Jul 27, 2024

Mucha teoría, poca práctica.

By Sumit S

•

Nov 14, 2022

good experience

By Lior G

•

Dec 28, 2024

i had a lot of problems in the grading even when i was right

By Pranav G

•

Apr 2, 2023

i didnt get to avail my certificate, though it was showing last submission date as 2nd april, i cant submit on 2nd and couldnt get my certificate

By Sanket P

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Sep 2, 2024

I have enrolled through financial aid but it is asking me to upgrade and pay for it

By Vivian P

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Mar 27, 2024

Class does not exist- the links do not work

By Harsh S

•

Jun 21, 2023

good course