MG
30 de mar de 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.
TG
1 de dez de 2020
I learned so many things in this module. I learned that how to do error analysis and different kind of the learning techniques. Thanks Professor Andrew Ng to provide such a valuable and updated stuff.
por Guilherme
âą5 de dez de 2017
The discussions on practical guides about designing deep learning systems, dealing with data, bias variance trade-off, and how to organize projects to optimize time usage are much needed for practitioners.
por Terrence G
âą12 de out de 2017
Practical advice for new students when tackling a real-world ML project and how to approach to optimize a model's performance. The quizzes provide good examples of use-case scenarios and decisions to take.
por Juan P A C
âą23 de set de 2020
I think the simulations were great. They give an excellent approach to real life enterprise scenarios where you have to take important decisions. Great compliment for the first two courses of the program.
por Harshal R P
âą31 de mai de 2020
Step by Step approach to structure Your Machine leaning project from scratch. The cherry on the cake is simulation quit provided at the end, helps quite fast to get the practical approach to the problems.
por Anurag C
âą5 de dez de 2019
This course is very helpful to fine tune our machine learning and our deep learning projects and probably more input to the different types of transfer learning examples could have been much more helpful
por Mustafa A
âą1 de dez de 2019
I love it. it was very helpful but I think if it was an assignment "programming assignment" with some issues "mismatch, incorrect labeling, .. etc " and use those techniques it would be much more helpful.
por Mohamad K
âą2 de dez de 2018
Its most great and important course ever, please try to listen very carefully to Prof Andrew, he tell you about each and everything you need to become master in ML. Many thanx for Prof Andrew and COURSERA
por Sudip B
âą4 de dez de 2020
I really enjoyed taking this course. The use cases and practical strategies to the problems were really insightful. I'm really excited to apply what I learnt from this course on my own personal projects.
por Romayssa B
âą10 de set de 2020
I learned a lot of new methods to structure not only deep learning projects but also ML projects. Very interesting and gives a wide overview of how we can improve our project management in AI in general.
por Frantisek H
âą4 de set de 2020
Excellent course - Andrew's teaching is what's so needed in the machine learning community. He explains concepts properly so that one truly understands them, and thus knows what to do when applying them.
por Islam W
âą7 de jun de 2020
Prepare you for the problems faced in machine learning projects, I'm now capable of analyzing projects for other people although I'm only in the path of Machine learning for 40 days.
Thank you, Sir Andrew
por Muzammil
âą18 de mai de 2019
I believe Andrew Ng shared some key insights into building successful machine learning projects. I really enjoyed the course and believe the shared information to be invalueable for my further research.
por Rajesh C
âą15 de out de 2018
This is the most important course of all the machine learning courses from deeplearning.ai. I learned in two weeks, what normally will take years of experience from this course i.e. ML project strategy.
por Aleksandar S
âą5 de fev de 2021
Well structured course for structuring machine learning projects. I've looking forward to go more with similar learnings. It is very helpful to expand an idea. Shortcuts with projects are promised here.
por Patrick F
âą25 de jun de 2020
That course is so valuable in order to drive into a ML project. Especially, the project life-cycle simulator are really awesome to practice model diagnostic and what to do next !! Really amazing module!
por Rohan S
âą17 de abr de 2020
A very unique and practical-based course that really shows the intricacies involved in making a machine-learning project and Andrew has really provided with hardcore lessons from his enormous experience
por Govinda N D
âą30 de out de 2019
Course is really useful in explaining which part to focus on to reduce the error and how to detect which part of algorithm should be given more time to reduce error and improve performance of algorithm.
por peter b
âą3 de set de 2019
A bit more theoretical this time. But the information is worht the time. I think that the knowledge Andrew is spreading will make me more efficient in my AI jobs ahead. At least I hope and think that :)
por Craig M
âą6 de dez de 2017
Andrew Ng's excellent teaching style leaves you with an intuitive understanding of machine learning setups and potential pitfalls. For me it's the best way to learn; this stuff really sticks in my head!
por Esteban J R
âą23 de abr de 2021
Incredible course, so full of practical advice from Andrew Ng. Ah, and speaking about transfer learning, I cannot stop surprising myself of Andrew's ability to transfer his learning from him to others.
por Gaetan P
âą12 de jun de 2020
Very well structured course about all the little tuning things to be done to actually make a machine learning algorithm work well. It is really a course to be taking as part of an overall ML formation.
por Wilem
âą24 de nov de 2019
Really interesting!
We used to be concerned about unbalanced train/dev/test, and with this course I realised this are not the main problems for achieving performance in ML
A master class.
Thanks Andrew!
por William G
âą14 de jul de 2019
not as technical as the first 2 courses in this specialization (and the next 2 for that matter), but it is still a well rounded course and highly recommend to do all the courses in this specialization!
por Karthik V
âą11 de set de 2018
Extremely interesting and useful practical advice that can help make significant difference when thinking about how to identify and correct problems. The quizzes were fantastic and made me think a lot.
por Ernesto N S
âą4 de dez de 2017
Excellent material. I would say this is the most important course of this specialization. Knowing how to approach a certain problem can indeed save us a lot of time and help us avoid a lot of mistakes.