Mar 31, 2020
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.
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.
por Elias A•
May 27, 2020
Don't let the lack of programming exercises fool you into thinking this isn't as important as the other courses in this specialisation. Professor Ng offers a summary of years of ML experience, as well as a sneak-peek of real world projects and how we should tackle them.
por Jk L•
Nov 29, 2017
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!
por Sasirekha K•
Jun 12, 2019
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.
por Marcel M•
Jun 01, 2018
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.
por Chuong N•
Apr 08, 2018
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.
por Badr B•
Feb 09, 2020
Professor Andrew Ng was astounding in the way he explained the concepts, also, like the famous machine learning course, all of the courses in this specializations were great in terms of quizzes and assignments that help have a complete grasp of the subject. Thank you.
por Gerald B•
Feb 28, 2018
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.
Nov 08, 2017
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!
por Alejandro J M R•
Sep 10, 2019
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.
por manideep s•
Jul 21, 2018
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.
Nov 19, 2017
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...
Oct 21, 2017
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!
por MOHD F•
Jul 23, 2019
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
por Kunal N•
Feb 18, 2018
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.
por Anurag A•
Sep 11, 2017
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.
por Akshat J•
Apr 11, 2020
Once a person has a knowledge of how to become a developer in the prevoius courses, this course gives you the knowledge to escalate from developer to a project architect. It teaches crucial techniques required to guide the training model to produce better result.
por Selim R•
Nov 19, 2017
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
por Fahimul H•
May 31, 2020
This was a much needed course after the 2nd one in this specialization! This course provides a clear and essential picture that is needed during development stage as well as shows the scopes of applying different techniques/blocks that were taught in course two.
por Raul T•
Oct 09, 2017
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.
por Tolga B•
Jun 23, 2020
Very well structured (pun intended) and informative course! Andrew makes a fantastic job transfering his knowledge to his students. I gained very much insight in general for prioritizing different tasks in machine learning projects and planing the future steps.
por ISAIAH H A•
May 22, 2020
This class, although short, was very interesting and serves as a useful guide to aid in building a deep learning model from scratch. The quizzes are really interesting as well as it makes you think about a step-by-step process in your own model implementation.
por Jay G•
Oct 06, 2018
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!!
por Gillian P•
Mar 02, 2018
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
por Kyung-Hoon K•
Nov 23, 2017
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!
por Matthias T H H•
Aug 27, 2017
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!