I loved this course. Although there wasn't any exercise other that quiz, this was pretty interesting and gave me a lot of ideas to try. I was wondering about how transfer learning would work before this, and now I know how it works! I am looking forward to the next course.

This course confirms the capacity of Andrew Ng to teach complex topics in a simple way. The course is full of advices and trick to structure and to success with machine learning projects. Suggested for people that already took courses on machine learning and deep learning.

Even after working in the field for many years, I find that I learn something new in every video. Andrew really captures well what is important from both practical and theoretical perspectives and is a master at explaining concepts in a simple, but not dumbed down manner.

I initially underestimate the value of this course. But it turns out that it gives very good insights on how to start tackling a problem with a DL mindset. Also, I learned about Transfer Learning and Multi-Task learning which I think its an amazing plus from this course.

I want to recommend this course because from it I get knowledge that can explain some of the confusions during my experience of building ML projects. I think in all probability I will encounter much more troubles if I've not got this course. Thanks, Andrew and Coursera!

This course is a fantastic guideline to some very real problems that I am working on in the industry. Thank you, deeplearning.ai team, for breaking down research practices into more definable steps. I already see how I can be more efficient in solving some DL problems.

This course is a solid continuum from the first two courses of this specialization. With the added twist of insider information from Prof Andrew Ng, a tried-and-tested practitioner of this Deep Learning art. The Machine Learning Simulation is pure genius! Ahsante Sana.

This is the most useful and unique course among all other materials of deep learning. It addresses the problem of trouble shooting for deep learning, which is the most daunting and mysterious. In fact, the note of this class will be a guide line for my future projects.

I enjoy Andrew's approach to managing AI projects. He hits on very real issues we encounter when young, enthusiastic scientists want to solve problems with ML, but get lost in the numbers and multitude of possible next steps to take top improve the quality of a model.

This course is a little bit hard for me, because I never heard these concept before. But through this course, I got a lot of new ideas to start my own machine learning project, and use these knowledge in practice. Thanks for the nice course and I will keep learning!

Esta fase del curso es de gran importancia para saber como encarar un proyecto de deep learning con sus mejores prácticas. El proceso iterativo de desarrollo es bien explicado y te permite construir la base de cualquier tarea de deep learning que vayas a emprender.

Though we learn different machine learning models to train, we might miss the logical key practices and struggle and waste lot of time while training to achieve better results. This course teaches those important practices to efficiently implement the ML projects.

Very helpful course. This course is very helpful that I got to know the things beyond the technical details of the neural network. About selecting test and dev set distribution, transfer learning, error analysis , end to end deep learning etc. Thank you Coursera...

I have learnt algorithms theory of machine learning and how to use them into data mining. However, I’m not good at ML strategy, so I can’t build a very well model. Through this course, I know many methods to improve models which I build before. Thank you very much!

Amazing Course ... different structuring strategies involving Orthogonalization, Single number evaluation metric, Carrying out error analysis, and how Cleaning up incorrectly labelled data including Transfer Learning are Beautifully explained by Andrew Ng...KUdos

The best part of this course was the "ML Flight Simulator" questionnaires (peacotopia, auto-driving). These real life examples and grading on that is the best thing. It helps you learn and interpret the concepts much nicer. I wish there were more of such examples.

This course has been really insightful into how we should work with machine learning projects. True, that most of the ideas discussed here are not covered in normal university curriculum. Thanks a lot to Professor Ng for coming out with this really helpful course.

I feel this is an extremely important course for all aspiring deep learning practitioners: being good is not only about knowing the algorithms and architectures, but also how to best manage your time and choose the most promising avenues to explore. A rare course

Shows methods for improving performance of deep learning setups in a time efficient manner. I like that deciding what to try next for improving a deep learning setup's performance is a recurring topic in Andrew Ng's courses. Knowing this can save a lot of time.

A fantastic course. I believe the strategies presented are practical and powerful in actually developing a deep learning system. I very much look forward to encountering those first problems and using these strategies to guide my model development. Well done!!

Great course covering topics that are not seen anywhere esle and are probably highly udnerestimated. The graded simulations are a very good idea that could be used in other courses as well. Professor Ng excellent performance is no surprise for anyone having fol

This strategic thinking for planning ahead will absolutely save tons of times of ML developers when building a real-world ML system. This course gave me a lot of thinking points, even without programming assignment. Thanks professor Ng, Mentors, and classmates!

Excellent course on how to analyze errors of machine learning applications. This material provides good ways to improve the speed of iteration over any machine learning project.

This class is unique as professors rarely provide this kind of insights. Thank you!

Worth the time and effort. Although this course did not contain the programming aspects, but it was helpful nevertheless. This course actually taught me how to properly go about my machine learning project and how to troubleshoot if I encounter some problems.

This course give me direction to structure my project in better way. Content of this course was really awesome and most amazing part was the flight simulator for machine learning. Thank you Andrew Ng sir for beautifully presenting the idea, thank you so much.