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Learner Reviews & Feedback for Machine Learning by Stanford University

4.9
stars
165,606 ratings
42,419 reviews

About the Course

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you'll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems. Finally, you'll learn about some of Silicon Valley's best practices in innovation as it pertains to machine learning and AI. This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI). The course will also draw from numerous case studies and applications, so that you'll also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas....

Top reviews

BK
Jul 11, 2021

I've learned a lot from this machine learning course. A huge thanks to prof. Andrew for guiding me throughout this course, and also Coursera for providing me with such a platform to learn this course.

QP
Jun 24, 2018

This course is extremely helpful and understandable for engineers and researchers in the CS field. Many thanks to the prof. Ng Yew Kwang for his great course as well as supporters in the course forum.

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51 - 75 of 10,000 Reviews for Machine Learning

By Rafael d S P

Jun 10, 2020

This is a great way to get an introduction to the main machine learning models. The professor is very didactic and the material is good too. I recommend it to everyone beginning to learn this science.

By Mehdi A

Feb 24, 2018

Too many trainings and assignments without enough practice, exercise and examples. This can be very confusing for a person taking the course for the first time.

By Jimmy C

May 18, 2019

I‘m a Chinese post-graduate student of Computer Sciense. This class is very useful to me because of it's amazing course videos and the well-designed programming exercises. It is really lucky to have this opportunity to find the course and to finish it. This class will be a footstone for further studying in AI field for anyone who just get started.

By Roman

Feb 12, 2021

I would not recommend this course anymore in 2021 since it is almost 10 year old now and it really shows! While essentially a good starter for machine learning, this course spends way too much time elaborating simple and obvious concepts while completely skipping over most mathematical explanations or more in-depth explanations of the presented topics. Furthermore, this course contains a myriad of errors in the presented slides, complete reluctance for any consistency in variable indexing (even in the same equations), painfully obvious editing mistakes, and the English subtitles are utterly useless. Seriously, a machine learning class with a gibberish as subtitles that was probably auto-generated using machine learning is irony at its finest.

By Bayram K

Feb 17, 2017

I would rename this course as Programming Octave with Application to Machine Learning rather that Machine Learning. Once you start the course you will have to focus on Octave rather than on ML topics if you want to do programming exercises. There is no degree of freedom in programming. You are provided with a lot of weird Octave codes which you will have to complete instead of writing yourself from scratch. More than 50% of my time was spent in order to learn Octave and understand (guess!!!!) Octave codes.

So, if you really want to learn ML and try it in practice this course is not for you. However, you could just watch the videos whose level is not more that elementary introduction to ML.

By Prabhu N

May 28, 2019

Course content was awesome, gave me lot of insights. If assignments were in Python, it would have helped a lot to improve my skills. Anyways I would recommend this course to a beginner who wants to understand the logic behind the machine learning process. Thank You AndrewNg Sir!!!

By Rune F

Dec 18, 2016

Fairly good videos explaining the material, probably worth 4 starts. However, the written support material should be improved. IMHO the video should supplement the written material, i.e. it should be possible to learn the material only by reading. This is not the case, so frequent pausing of videos and making lots of notes is needed if one wants to commit this course to long-term memory.

By Anton D

Apr 24, 2019

Overall, this is a great course and I learned an enormous amount of information. The biggest issue I had was the disconnect between the course and the assignments/quizzes. Although they had help sections, because you couldn't ask direct questions about the algorithms/quizzes, if you had a problem, you were basically on your own. (At least that is what it felt like.) For example, if you missed a quiz question and couldn't figure out the answer, there seemed little recourse to find the actual answer. In a couple cases, I decided to just take the 80% on a quiz simply because I had no idea what the answer was.

By Herman v d V

Jan 15, 2019

My first open online course from Stanford University gave me a lot of energy. As my student years are far behind me (I am 76 years old) it was a discovery to become enthusiast in this new area. And building on my career in ICT, this is a surprising extension on the way systems can help us to develop a better life. Professor Ng is very good in offering in a controlled way many insights in the machine learning - now it is time for me to apply my new knowledge!

By Andrey

Jul 24, 2019

This is a very basic course on Machine Learning. The main drawbacks are:

(1) the material is old and not updated to reflect new developments in this dynamic subject;

(2) the course is oversimplified and adapted for students who have never dealt with maths or programming;

(3) the assignments and quizes are, with rare exception, trivial and test students' common sense rather than the subject understanding; for example, you can pass the final quiz at 100% without reading or watching the lectures;

(4) the course is badly maintained: some mistakes in lectures and assignments have not been corrected for years, even though they have been pointed out in the discussion forum countless times.

While the Ng's ML course is arguably better than many other Coursera courses, it is very disappointing that Coursera and Stanford hardly made an attempt to improve it.

By Rui L

Oct 1, 2018

I would not recommend taking this course any more. (2018)

This course is showing its age and lots of concepts simply doesn't apply any more, considering how fast this field is changing.

By Subham B

Aug 30, 2019

This course is definitely not for beginners.

By Ali F

Mar 17, 2021

I want to thank you very much for such a great course in any aspect especially from professor Ng . I just want to suggest that it would be great if there was a final project for the end of the course.

By Pardis J Z

Jun 30, 2020

I really enjoyed this course. I learned new exciting techniques. I think the major positive point of this course was its simple and understandable teaching method. Thanks a lot to professor Andrew Ng.

By zhang w

Apr 2, 2018

Very nice course,. Give a fundamental knowledge of machine learning in a clear, logic and easy-to-understand way. Suitable for those who has relatively weak background of math and statistics to learn.

By priyanka h

Sep 16, 2020

Loved the course. Andrew Sir explains the intuition behind the concepts really well. Excited to continue with the rest of the courses by him on my way to becoming an AI Engineer.

Thanks a lot, Sir!

By Prateek J

Jan 21, 2019

Exceptional. Best course to start learning Machine Learning! Only one grouse though, the exercises are in Matlab and not in python.

By Hu L

Feb 14, 2018

Too easy and too slow

By Reinhard H J

Oct 18, 2019

The course content is vastly outdated and superficial.

By Seth W

Nov 9, 2020

Excellent course, highly mathematical overview of how introductory machine learning models work. Thanks to Andrew Ng for putting together a lot of great material and challenging quizzes and exercises.

By Kevin H

May 23, 2021

Programming exercises focus on the topics and provide you with good templates that you can easily fill in so you don't waste your time. Videos are very well done and quizzes are reasonable difficulty.

By Juan J G P

Oct 25, 2016

Great course. A progressive discovery of the maths inner to the learning algorithms. This course gives that insight many ML practitioners don't have and is so important for making real use cases work.

By Hou Z

May 4, 2019

Very good instruction for machine learning, and also very very good for new comers!!!

By Nikhil J

May 18, 2019

It was a great learning experience. All the lectures were in details.

By Aditya K

May 18, 2019

It was a very helpful course.