Nov 23, 2017
I learned so many things in this module. I learned that how to do error analysys and different kind of the learning techniques. Thanks Professor Andrew Ng to provide such a valuable and updated stuff.
Mar 19, 2019
Though it might not seem imminently useful, the course notes I've referred back to the most come from this class. This course is could be summarized as a machine learning master giving useful advice.
por Hanbo L•
Sep 22, 2019
Good non-technical materials, but short enough to be incorporated into other courses. Some aspects feel subjective. Many typos/minor mistakes in quizzes
por Anne R•
Sep 25, 2019
Good general information is provided but this material could be layered into the other courses in this specialization. I would recommend that the case studies be based on real industry problems that present the backstory of the decisions the teams made. Also programming assignments would be useful in which the impact of incorrectly classified training data is studied in detail or in which images that have been synthesized are used versus not used. It did not take too much time to work through this course so the information provided is worth the cost, but I am not convinced that this series is viewed as more than an opportunity to make some money off of the name brand. Much of the information provided so far is covered in the Deep Learning - Goodfellow text and the extras are vague and repetitive.
por Kanghoon Y•
Sep 04, 2019
I got an intuitions from this lectures. But What I want to get from this lecture when I first saw the title, is the method how we can define the activation function at multi-task learning etc. In this video, I got only the overall flows.
por Jose P•
Sep 30, 2019
Topics are a bit vague, which is fine as the content is interesting and useful nonetheless, but perhaps exposition is too lengthy relative to the amount of content.
por David R•
Oct 01, 2019
Overall the courses in the specialization are great and provide great introduction to these topics, as well as practical experience. Many topics are explained clearly, with valuable field practitioners insight, and you are given quizzes and code-exercises that help deepen the understanding of how to implement the concepts in the videos. I would recommend to take them after the initial Andrew Ng ML course by Stanford, unless you have prior background in this topic.
There are a few shortbacks:
1 - the video editing is poor and sloppy. Its not too bad, but it’s sometimes can be a bit annoying.
2 - most of the exercises are too easy, and are almost copy-paste. I need to go over them and create variations of them in-order to strengthen my practical skills. Some exercises are quite challenging though (especially in course 4 and 5), and I need to go over them just to really nail them down, as things scale up quickly. Course 3 has no exercises as its more theoretical. Some exercises have bugs - so make sure to look at the discussion board for tips (the final exercise has a huge bug that was super annoying).
3 - there are no summary readings - you have to (re)watch the videos in order to check something, which is annoying. This is partially solved because the exercises themselves usually hold a lot of (textual) summary, with equations.
4 - the 3rd course was a bit less interesting in my opinion, but I did learn some stuff from it. So in the end it’s worth it. Not sure I would have taken it as a stand-alone course, though.
5 - Slide graphics and Andrew handwriting could be improved.
6 - the online Coursera Jupyter notebook environment was a bit slow, and sometimes get stuck.
Again overall - highly recommended
por Shivam K S•
Oct 01, 2019
Could have been more in depth or could have been added to another course as one extra week
por Sajal J•
Oct 29, 2019
por Marco L S•
Nov 28, 2019
Useful but not that much for assigning to those topics a course of their own.
por Bjorn E•
Sep 09, 2019
Interesting and practical information, but it felt stretched out in an attempt to create a two-week course. With some editing and less repeated information this could be one week that would fit in the prior course.
por Vincent P•
Aug 24, 2019
Was really enthousiastic about the first two courses in the specialization, the third however felt a bit like going back a step in level of advancement.
por Patrick F•
Dec 12, 2019
Seeing different practical use scenarios and adaptions is fine but it got pretty boring without a real application to tune. The Quizzes on the other hand were very good!
por Sean L•
Oct 06, 2019
por Wayne S•
Sep 01, 2019
Video lectures tend to be repetitious, and can be confusing.
por Michael L•
May 02, 2018
No programming assignments or labs, so too much theory, and too little chance to put same into practice. Not a good value for my money.
por Daniel D•
Sep 04, 2017
The course es good, but it seems still under development.
por Jonathan C•
Aug 22, 2017
There's some very good tips in this course, but it's not enough content to even warrant the two weeks that's it's spread out over. It would have been high quality material as a part of another course or as an addendum, but it hardly stands alone by itself. Unfortunately, that seems to be the trend on Coursera to provide sparse content spread out over multiple courses to milk money. Entire specializations could be fit in one course but now it's 7. Viewed in context of this specialization, a lot of what Andrew Ng lectures on seems to be padding to lengthen the videos since he tends to repeat the same points over and over and over. In other words, a lot of what Andrew Ng lectures on seems to be padding to lengthen the videos ... see what I did there? Maybe I can get a job at Coursera?
por Wouter M•
Jun 13, 2018
A bit short
por Duncan K M•
Nov 20, 2017
I like coding projects and hands on material, this was heavy on the videos
por Fabian A R G•
Oct 29, 2017
Even though the materials in the course are very interesting, I would expect that in the third course we would have more tools in order to work by ourselves in a project... It would have been amazing a final project where you can put together this tools. Nevertheless it is still an interesting course.
por Joseph A D•
Jan 28, 2018
Helpful guidance but I didn't get enough material to help *me* generalize what I learned.
por Francisco S R•
Oct 25, 2017
The course was just a bunch of tips and suggestions. Yes, they are useful, but given the empirical nature of machine learning I would expect those tips to be accompanied by practical applications and homework.
por Gaurav M•
Jun 14, 2018
It could be little shorter module
por Dany J•
Nov 16, 2017
Good content, but could definitely benefit from a more fleshed out problem to solve. The content beg for a larger concrete coding exercice project.
Jan 31, 2018
Good course to learn about structuring the projects and carrying out error analysis. I wish there were some assignment to work on in addition to the case study quizzes. Assignment really help us learn effectively
por SAGAR B•
Oct 30, 2017
The course work is really good. It has a practical emphasis. However, I did not like the quizzes (especially week 2 quiz) in the sense that the options are not very clear to understand and you end up being more confused. I hope the team works on the clarity of options for people who take it in future.