It is very nice to have a very experienced deep learning practitioner showing you the "magic" of making DNN works. That is usually passed from Professor to graduate student, but is available here now.
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.
It's a theoretical approach of Machine Learning projects that gives a lot of awesome insights of many real world problems that you face when building your model. It's a short course with great insights ! I definitely recommend taking it.
By Khaled J•
Excellent class with practical advise to accelerate the application of best practices based on Andrew's experience. I would highly recommend this to practitioners wanting to save a lot of time learning these best practices the hard way.
By SUJITH V•
Excellent course on understanding how and what to prioritise in ML projects. Not just helpful for people leading ML teams, but also for people who are doing some independent projects. ML is a lot of fun when you do experiments for fun :)
By Mohamed C S•
Excellent Course, though it is an optional course, it is really worth taking it!
The Use case studies are just excellent! You can really have a taste of the problems encountered when you have to manage a deep learning project. Great work!
By Omid M•
Minor issue: often the request for feedback for a lecture came right at the beginning of the lecture, covering big portion of the video ('was this video helpful'! ). It was annoying (I couldn't figure out how to minimize it).
By Ashish P•
Amazing course. This course is really a practical understanding of what DL is. Apart from learning the algorithms practical aspects are very necessary for DL and this course provided me with the same.
Thanks to ANDREW NG for this course.
By Long C•
Great and detailed strategies especially for people working on a machine learning projects. With good strategies, time and money may be saved. A really good complimentary material to Andrew's new digital book: Machine Learning Yearning.
By Aditya G•
Highly recommended as it helps one think how to improve their ML models. Just do a 60/40 split and hoping for the best result is not the way to go, and this course definitely helps unveiling how to remove bias and variance from a model.
By Chulhoon J•
this course has very practical and helpful advices to solve problems related to the deep learning algorithms. I believe those valuable advices and tips will be able to reduce tremendous times and efforts when you stuck with the problem.
By Alfred D•
One of the best tips to use in real ML consulting projects; Prof Andrew Ng is an awesome teacher
and keeps you engaged , by giving relevant industry use cases for each topic being taught; This
brings objectivity and motivation to learn.
By Ketan D•
Best course so far in specialization as technical stuff you can google and get tons of books and blogs for . But for real world insight into how to solve problems is a great thing to know and not easy to find out from other resources .
By Marcin S•
If it were possible I would give 6 stars! The most valuable deep learning course I'v ever seen. There many more technical courses but related knowledge can be found in books/on lectures. Knowledge learn from this course is exceptional.
By Hisham R•
Actually, the information in this course were very valuable since they could be only gained after long time of real practical experience. Transfer learning, multitask learning and error analysis topics are priceless. Great course IMO.
I think it will be more helpful for those who have actually worked on real ML project,for me, it's still kinda abstract and a little boring except for the week 2 ,so it's worthwhile to learn it again once I get some experience in ML.
By Ihor F•
Course is time-consuming because it with high concentration with information. Would be maximum useful for those who have some experience in machine learning.
I am very excited! Quizzes are so interesting and close to real life project.
By Mcvean S•
An exceptional course to hone your skills, and develop efficient Machine Learning and Deep Learning systems to better address the problems faced in the real world. The added experiences of Andrew are an asset to the learning journey!
By Abe E•
Really useful quiz questions. I liked this class a lot even though there were no programming exercises. Getting some insights into the facial recognition and image classification stuff before course 4 was also really nice. Thanks! :)
By Eugene L•
Good course with a lot of qualitative information that is quite useful. Giving it a 4 because it would have been great if there were accompanying Jupyter notebooks. It's a solid course overall and I recommend it to anyone interested.
By Prakhar D•
This course is highly intuitive, practical and less mathematically complicated. Prof Andrew Ng uses many examples to elucidate concepts. Post learning one will be capable of choosing which direction to go in solving an ML/DL problem.
By Kadir K•
This was a great lecture from Andrew Ng. I have learned basics of error analysis, multi-task learning and structuring a machine learning project in general. This will be very useful staff for my professional career. Thank you Andrew!
By Virginia A•
Excellent point of view. many teach you how to do /write code to apply ML to your problem. in this course I felt they were teaching me how to understand the results and how to improve it. Extremely interesting for potential Managers
By Hugo T K•
This course is exceptional since we can learn a lot with Andrew Yang's great experience with Machine Learning Projects. It'd also like to suggest to add new classes about powerful and newer techniques, such as feature visualization.
By Prashant T•
These are most toughest things, in which people takes 100 of hours to explain and still people confuse. But by doing this course within a 4 hrs span you will have a decent knowledge. Kudos!! to entire team and thanks a lot AndrewNG
By Antonio C D•
This course covers lots of practical advice and techniques resulting from real world project experience by the author. I highly recommend this course to anyone involved in deep learning projects, even if not in a technical position
By Sai K•
this course very important other than previous courses because we need to understand the data and split the data set across the train, dev and test and making strategies for training the dataset using model. Thanks for this course.