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.
While the information from this course was awesome I would've liked some hand on projects to get the information running. Nonetheless, the two simulation task were the best (more would've been neat!).
por Akhil M•
Lot of info. A bit more practical programming approach to these issues would've been helpful but great way to put convey that information nonetheless!
por eddy k•
excellent practical and insightful strategies from years of andrew's experience, i wish there were more hands on labs to practice some of the concepts
por Amey V•
This course is a must-do, this course gives you the necessary confidence to go ahead and actually start building your own application and work on it!
por Robert P•
The content is well worth going through. While the "flight simulator" approach was certainly beneficial, I wish there had been programming exercises.
por Felipe M•
The course is good, as I would expect of Andrew, however, I feel like the standards of editing the videos has fallen quite a bit since the ML course.
this course was a little boring, but it covers all the necessary concepts about the error analysis and strategies to be followed in machine learning
por Cristian M V V•
The course walks you through different effective ML strategies. I'm holding the 5 stars just because I expected to see some hands on assingments.
por Nicolás M•
Overall a great course. Some of the quiz questions are very hard because the corre3ctness of some of the available options is quite a bit “fuzzy”.
por Rafiul H N•
The course has given me insight about the handling of ML projects. But it would be great if there was some CODING and specific algorithm involved.
Good course! Focusing on strategies on how to start well and manage a DL project.
But very vague! Hoped to have more thery & a usecase on the topic
por Frank H•
I had some problems answering some questions correctly since there was no specific emphasis in the lectures and I was somehow unsure how to reply.
por Gokhan A•
It has nice discussions on the practical aspects of Deep Learning projects, but I wish it had more Math, and it had more programming assignments.
por Kit B•
Thorough and well taught course on strategy in ML. Would have enjoyed some programming exercises, but the assignments served their purpose well.
por Bradly M•
This course was relatively short, and the quality of the materials (lecture videos, quiz text) was somewhat poorer than in the previous courses.
por E. M S•
Good practical advice. I would have added something about agile development and possibly practical advice on NN architectures (depth and size).
por Eloi T•
Excellent content but the quizzes are badly done, many questions have several reasonable answers and very little feedback if we 'get it wrong'
por Sujay K•
The course would have been more interesting if we had some programming assignments. Hands on experience into some of these cases really help.
por Daniel M•
Unique course in the sense that teaches important topics that are rarely seen in the literature and are fundamental in designing AI projects.
por Hagay G•
Had some pretty great info for junior Project Managers, for some reason, it's also hiding some extremely important info about end-to-end DL.
por Mohamed M H M A•
Some of the videos weren't of good quality. Also, I was expecting doing a real project not to make decisions based on different scenarios.
por Nikolai K•
Good course overall, would have liked to have the in-depth programming assignments though, those really made the other courses stand out.
por Shashank S S•
Learned various ways to structure ML projects in industry.
It would have been great to have few programming assignments included as well.
por Leonid M•
Some tips are very useful for practitioners but the same information is repeated over and over again that makes the course quite boring.
por aman a c•
A small course with very effective tips and tricks to figure out how to start and proceed further while building a project effectively.
I think this lecture is very useful when we make our own ML system.
Also, it has many examples about errors we can usually meet in real.