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 08, 2018
Going beyond the technical details, this part of the course goes into the high level view on how to direct your efforts in a ML project. Really enjoyable and useful. Thanks for making this available!
교육 기관: Alexandru S•
Sep 08, 2017
Very interesting material covered - not too many courses have this kind of information.
A little too short and very no practical assignments (only quizes). It would be very useful (although I agree quite time consuming to prepare) to have some programming assignments that deal with the topics in the curse.
교육 기관: Ernst H•
Jul 09, 2019
4 stars for a very good course that should be improved. Course is still good, but it is not as polished as the first courses in this series. I rated those with 4 stars, too. There are mistakes in the quiz names, grammatical errors in quiz questions, etc. Never-the-less, it is the best of its kind.
교육 기관: MIchael•
Nov 19, 2017
The insights could be visually structured a bit better so that I can also check them after the course as a reminder.
Often recommendations like if then could be put in processes or cheat sheets
overall: very valuable course regarding the insights and encouraging style of Andrew Ng
교육 기관: Burag C•
Apr 10, 2018
This was a good intuition course. I learned a lot and loved the content. However, I am afraid the information here needs to be repeated many times to make it a habit (as part of programming exercises). That's why I am giving it a 4-star. I feel like this could have been part of the last course.
교육 기관: Kevin C•
Dec 22, 2019
Great overall. However, a major thing that is missing is the different between val set and dev set, and about the recent trend to perform K-Fold CV on the training set to get the val set. Maybe still need a separate dev set because of the different distribution if it comes a separate soure?
교육 기관: Anthony•
Nov 15, 2017
Wish there were more projects / assignments to exercise concepts taught. Like in the first 2 courses of the specialization.
Maybe even blending videos with a broader Jupyter notebook would be better. The videos are great, but paired with practical application its much more likely to stick.
교육 기관: Prashant S•
Mar 02, 2018
-This course have two quizzes and no programming assignment.
-This course gives a very good advice on how we can improve Algorithm performance.
-Best way to split data into Train/dev/test.
-Quizzes statement can be made more precise and clear but stil the scenario in the quiz was good.
교육 기관: Timo K•
Dec 20, 2017
Very good course, but in contrast to the other courses the practical exercises are missing. I would like to see some transfer learning and (non-)end-to-end learning approaches, where the student has to examine how bad/good end-to-end performs in contrast to a multi-step approaches.
교육 기관: Samchuk D•
Sep 24, 2017
The content of this course is quite unique. Thus it makes it much more interesting and important.
Thank's a lot for this tips!
However it would be nicer if there is some videos practical assignments about tech aspects of implementations of "transfer learning" and "multitask learning"
교육 기관: Eslam S H•
Aug 20, 2018
I got the same feedback for many of my colleagues that this course is not that important and I should start with course #4 instead, but I am glad I didn't there is a lot of insights and experiences in this course that I think it would take anyone many years to conclude by himself.
교육 기관: Milan S•
Jun 01, 2018
Sometimes its become bored who has not any experienced into working on real life ML project because without facing problem you can not understand problem in better way so i recommend course instructure to make this course with little more practical way so that it easy to digest.
교육 기관: Hans E•
Feb 18, 2018
A bit slow going and repetitive (and some simple video editing to remove double sections would improve things). Nevertheless I'm amazed how much I learned or consolidated is just a few evenings of watching these videos. Thanks again! Looking forward to course 4 in this series.
교육 기관: Srinivas K R•
Oct 03, 2017
Thorough and practical guidelines to structure and analyze issues with machine learning projects. Distilled learning presented from a lot of project experience. It would be hard to gain such knowledge without having gone through a number of projects. Accelerates your learning.
교육 기관: Rahul D•
Apr 20, 2019
Machine learning simulator assignments were great, wish we could have more of them both in this course as well as in the other courses in the specialization. Additionally, I would have loved programming assignments that reinforced these largely workflow-related concepts.
교육 기관: Lester A S D C•
Jun 25, 2019
Useful knowledge regarding the efficient practices in the application of machine learning. Mentors doesn't seem as responsive though, compared to the other courses of the specialization. Quizzes were helpful, but needs more justification for some of the correct answers.
교육 기관: Harshit S•
Nov 12, 2017
The course showed the experiences while dealing with machine learning projects but could have been better if the experience would have been shared through practical exercises rather than objective case study.
It would be better if there were programming exercise as well.
교육 기관: Jihwan M•
Sep 15, 2017
I have a feeling that this third course is not yet fully edited. I see some black screens, and sometimes the clips have Andrew speak faster than usual. Nonetheless, the various tips and appropriate actions to take when doing a machine learning project were very useful.
교육 기관: Akshaya R•
Jan 12, 2020
Good explanation for the initial steps of organizing the ML project and the direction to approach the problem accounted for. The quiz was interesting but as it is the same set of questions for any next attempt, I would not say I have mastered the course completely.
교육 기관: Jean-Simon B•
May 08, 2018
Only 2 weeks, good concepts to know. But videos are not "final release" they are not well edited. Some time Andrew repeat the same sentence 2x but they forgot to cut it.
No programming assignment. Although quiz format is fun and you really learn by doing the quiz.
교육 기관: Bogdan P•
Sep 03, 2017
This was a slightly more theoretical course than the first 3 in the Deep Learning specialization and, even thought I enjoyed it, I think the info would stick better if there would have been a programming assignment too (or some other type fo practical application).
교육 기관: Kalle H•
Nov 20, 2017
Nice and concrete examples of what to think of and focus on when trying to improve your machine learning projects. Not as engaging tasks to complete as in the previous courses in this specialisation, however a good change of scenary if you have been doing these.
교육 기관: Boris V•
Jan 21, 2018
Great material, but it's not quite easy to understand it from scratch, if you didn't have such problems yourself (i.e if you have no experience in deep NN training). I've stored this material and going to revisit it after I gain more experience in training NNs.
교육 기관: Fredrik K•
Oct 06, 2017
Great course, however the quiz of week 2 had some ambigious phrasings and I think at least one example (the one with the data synthesis of foggy images) is contradictive of what was taught in the video lessons. Other than that, really good content and teaching!
교육 기관: Bharath N S•
Apr 20, 2019
A lot of concepts were put forward and taught well. If there was a programming assignment as well to back up the concepts that were taught like multi-task learning, how to deal with data mismatch, dividing the total data into train\train-dev\dev\test data etc.
교육 기관: Eemeli L•
Nov 19, 2019
Great and easy-to-follow introduction to structuring machine learning projects and focusing on what to tune on neural networks. One star left out because the content has not been polished, but there are minor errors here and there with separate corrections.