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

4.9
stars
3,837 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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576 - 600 of 611 Reviews for Unsupervised Learning, Recommenders, Reinforcement Learning

By Farouk B

Sep 28, 2024

very good course but it needs lab practice , it looks like we just run the code , aand if we want to write by our self it is hard . but thank you so much

By José L F G

Jan 7, 2023

Very instructive and interesting. There were some videos were the slides were very cluttered with calculations (e.g., the derivative optional video).

By Vikas S

Mar 18, 2024

The lab assignments are feel happy in nature. They should force the learner to write more than just the code for hidden layer selection. Thanks!

By Arsam A

Jul 12, 2024

the content and theory are very good in the course, Andrew is an amazing instructor I just wish there were more coding exercises.

By Santosh R

Jul 1, 2024

All the contents were excellent except reinforcement learning. The videos seems very less and not very understandable.

By Aminreza N

Nov 7, 2024

thanks for the course, I just feel in some subjects we could deep more to the mathematical aspects of subject.

By Raghavendra N

Aug 2, 2022

Great course on understanding key machine learning techniques without getting too deep into the mathematics.

By jaime k

Sep 1, 2024

It felt a little rushed compared to the previous 2 courses. Still really good, but it doesn't go as deep.

By Marc A

Jun 5, 2024

The labs are not very challenging, maybe some more coding would help to understand more material.

By Derk v G

Dec 15, 2022

Nice content, the speed of speaking was a bit slow. Fortunately I could watch at 2x the speed.

By Miguel M

Jul 16, 2024

It's a good course for complete beginners, but a bit lacking in practical exercises

By Alejandro S

Jul 9, 2023

The course needs more application excersices and no just the theory of the concepts

By Yash B

Dec 29, 2022

great course but practice labs weren't challenging nor tested material well

By Janardhan P P

Jan 24, 2024

few topics were little complicated , specially reinforcement algorithm

By Mario

Feb 16, 2023

great course and content

The reinforcement learning part can be better.

By Hrishikesh K

Nov 9, 2024

It would have been better if the assignment were a bit more tough.

By Mayank D

Dec 10, 2023

the practice assignments were very disturbing and took lot of time

By Wassim R

May 31, 2023

Thank you.

I suggest adding more optional labs before practie labs.

By Lior G

Dec 1, 2024

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

By KUSUMLATA K

Nov 24, 2024

The assignment are very useful and informative, thanks alot.

By vaibhav v

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

Nov 19, 2024

Me gustaría que hubiera mas ejercicios prácticos.

By Vasanthan B

Aug 20, 2024

Excellent curriculum for AI/ML beginners.

By Abhinav P

Jan 7, 2024

wish it were more implementation focused