Oct 26, 2017
Amazing course for people looking to understand few important aspects of machine learning in terms of linear algebra and how the algorithms work! Definitely will help me in my future modelling efforts
Aug 13, 2019
Andrew Ng is a great teacher.\n\nHe inspired me to begin this new chapter in my life. I couldn't have done it without you\n\nand also He made me a better and more thoughtful person.\n\nThank You! Sir.
von Hou Z•
May 05, 2019
Very good instruction for machine learning, and also very very good for new comers!!!
von Nikhil J•
May 18, 2019
It was a great learning experience. All the lectures were in details.
von Aditya K•
May 18, 2019
It was a very helpful course.
von 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!!!
von Rishav K•
Aug 20, 2019
It is the best online course for any person wanna learn machine learning. Andrew sir teaches very well. His pace is very good. The insights which you will get in this course turns out to be wonderful.
von Abdul Q•
Mar 03, 2018
An amazing skills of teaching and very well structured course for people start to learn to the machine learning. The assignments are very good for understanding the practical side of machine learning.
von Kothala M K•
May 18, 2019
von 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!
von Brian L•
May 25, 2019
There's one saying in Chinese that says "一日為師，終身為師" which means once being someone's teacher, even just one day, you're the teacher for the rest of his life. Thank you for all your efforts and I really appreciate it. I'll keep working on Machine Learning and hopefully one day I can do the same contribution to the human society as you did.
May 18, 2019
Explanation was very good and assignment helps us to understand the real picture. The way course is planned along with octave exercise, Graphs and visualization of data (X,Y) is very good. Very good course who is starting the Machine learning from scratch.
von Fernando A H G•
Jul 21, 2019
Exceptionally complete and outstanding summary of main learning algorithms used currently and globally in software industry. Professor with great charisma as well as patient and clear in his teaching.
von Quoc-Viet P•
Jun 25, 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.
von Maksym M•
Aug 22, 2018
So much like it. It gave me starting push in this interesting topic. And one important thing that after this course I figured out I need to continue dive into machine learning.
von Akyuu F•
May 08, 2019
Excellent Machine Learning Lessons which need little advanced knowledge of mathematics.
von Spencer R H•
Feb 03, 2019
It would be nice if it's taught in either python or R. So I do need to take extra effort to learn octave.
von Harshal M•
Mar 25, 2019
If this course was in python or R it would have been easier to understand. Octave/MATLAB is not that widely used.
von Sergey K•
Jan 24, 2016
Level of difficulty of lectures is not correspond with level of quizzes. In lectures they are talking about simple stuff and then in quizzes they ask you about details they didn't mentioned. You could deducts this information though. But this is exactly the main problem with this course - for quizzes you should deduct and learn by yourself so much stuff, that videos start to be not worth your time.
von 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.
von Mathew L•
Sep 25, 2015
This course is absolute garbage. You get no feedback on your quizzes or assignments and the professor is one of the most boring I've ever seen. It's absurdly frustrating to repeatedly fail without any feedback as to why you're failing.
The lectures are clearly from a math perspective, as the prof simply draws what he's talking about on the slides. His hand writing is poor, and he does a lackluster job of explaining what exactly he's doing.
Finally, pure lecture with no notes is almost impossible to learn, as there's nothing to read and study.
I'd rate this course a 1/10, take the course on iTunes from Caltech instead.
von Rui C•
Dec 12, 2015
However good the material and lectures may be, the use of an outdated version of Octave (which is not Mac-friendly and exceedingly brittle, to the extent where the supplied code requires manual patching in Windows and Linux) is a complete turn-off and makes it nearly impossible to complete the assignments on time unless you're prepared to spend at least twice as much time debugging your setup as doing the actual assignments.
I'll come back when this is done with R or Python.
von Eric J•
Mar 27, 2018
Very well structured and delivered course. Progressive introduction of concepts and intuitive description by Andrew really give a sense of understanding even for the more complex area of the training.
von Marius N•
Oct 31, 2017
Great overview, enough details to have a good understanding of why the techniques work well. Especially appreciated the practical advice regarding debugging, algorithm evaluation and ceiling analysis.
von Karl M•
Aug 11, 2017
Very nicely explained the mathematical topics, even for people like me with some phobia regarding large formulas. Useful hands-on experience with MATLAB coding, which I would have had to learn anyway.
von Anup B D•
Apr 22, 2017
Very good coverage of different supervised and unsupervised algorithms, and lots of practical insights around implementation. All the explanations provided helped to understand the concepts very well.
Oct 15, 2016
It's a good introduction - not too complicated and covers a wide range of topics. The programming exercises are well put together and significantly help understanding. The free Matlab license is nice.