Chevron Left
Voltar para Structuring Machine Learning Projects

Comentários e feedback de alunos de Structuring Machine Learning Projects da instituição deeplearning.ai

4.8
33,626 classificações
3,522 avaliações

Sobre o curso

You will learn how to build a successful machine learning project. If you aspire to be a technical leader in AI, and know how to set direction for your team's work, this course will show you how. Much of this content has never been taught elsewhere, and is drawn from my experience building and shipping many deep learning products. This course also has two "flight simulators" that let you practice decision-making as a machine learning project leader. This provides "industry experience" that you might otherwise get only after years of ML work experience. After 2 weeks, you will: - Understand how to diagnose errors in a machine learning system, and - Be able to prioritize the most promising directions for reducing error - Understand complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance - Know how to apply end-to-end learning, transfer learning, and multi-task learning I've seen teams waste months or years through not understanding the principles taught in this course. I hope this two week course will save you months of time. This is a standalone course, and you can take this so long as you have basic machine learning knowledge. This is the third course in the Deep Learning Specialization....

Melhores avaliações

AM

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.

DC

Mar 08, 2018

Going beyond the technical details, this part of the course goes into the high level view on how to direct your efforts in a ML project. Really enjoyable and useful. Thanks for making this available!

Filtrar por:

3201 — 3225 de {totalReviews} Avaliações para o Structuring Machine Learning Projects

por Matt

Feb 15, 2019

The flight simulators' results were not consistent with the advice provided in the lectures. I'd suggest being either less black and white in the simulators' answer responses, or, being more polarised (more black and white) in the advice provided in the lectures. Otherwise, this is a 5 star course. Many thanks!

por Fritz L

Sep 24, 2018

I liked the course but it contained quite a few glitches which could be easily removed to improve the overall experience. E.g., once Prof. Ng makes a long pause and says "test". Sometimes the same ending is placed twice or in the final "Heros of Deeplearning" video Prof. Ng seems to ask the same question twice.

por Константин

Jun 09, 2018

This course compare to other was a bit boring to my opinion. But the whole specialization is great

por William K

Oct 10, 2018

Good and useful content. The staff should read the forum's errata section and make a bunch of fixes to the course though.

por Hasti K

Oct 03, 2019

It is a very useful course but I preferred to have a programming assignment as well to try what I learned.

por Trong-Tin D

Dec 04, 2017

Provide good strategies for building machine learning applications. Team leaders or managers may find it useful.

por Swann C

Oct 06, 2017

Very interesting topics so you can move onto managing Deep Learning Project more efficiently, saving time and

por Frederick

Oct 06, 2018

Batch Norm, Multi-task learning and transfer learning exercises were missing.

Flight simulator exercise was also missing

por Andreea A

Feb 16, 2019

Liking this course is subjective. It is indeed based on the experience of others, but since experience can't always be generalized and transferred, the lectures are repetitive and bland (they are also badly edited in Week 2). On the other hand, the two "ML flight simulators" are really interesting and answering them is not obvious. It requires a lot of thinking and focus to choose correctly from apparently equivalent solutions, which might happen in real projects.

por Sandeep P

Jun 24, 2018

The course appraises the reader of the various tricks that are needed to design nice machine learning projects. One minor suggestion would be to have some programming assignments for this course as well!

por Andrew W

Mar 13, 2019

Very slow, and probably longer than needed to be, plus only quizzes made it boring

por Saad T

Sep 07, 2017

I am a big fan of the jupyter notebook assignments. I can understand that it could be hard to build python assignments for this course, but not impossible I think (maybe around error analysis, impact of artificial data synthesis...)

por Mehmet N

Jan 04, 2019

Some questions/answers of the quizzes were not accurate enough.

por Umberto

Apr 05, 2019

useful hints and techniques to manage ML Projects and choose right approach

por Mahnaz A K

Jul 02, 2019

Thanks for the practical tips and insights from real projects.

Your pool of heroes of deep learning is very skewed. If the field is so skewed, then it's a bigger problem.

por Rajesh S

Nov 26, 2017

Lots of practical advice and ideas on how to work on actual projects and things to look out for. Great stuff. Wish it had a few programming exercises or a project.

por GOI C L

Feb 11, 2018

should have a real tuning example

por Brian S

Sep 27, 2017

Needs More Content

por Vivek V A

Feb 13, 2019

Good course for the ones who already started developing ML systems. This will help us in improving the ML systems and identify what can be done for which kind of problems

por Kevin R I

Sep 16, 2019

Not what I was expecting.

por Alexander Y B

Apr 24, 2018

Good for understand how to spend your time on DL projects I guess

por dh

Oct 17, 2017

provide student with some code tests like previous courses may be better .

por MIchael

Nov 19, 2017

Interesting insights.

The insights could be visually structured a bit better so that I can also check them after the course as a reminder.

Often recommendations like if then could be put in processes or cheat sheets

overall: very valuable course regarding the insights and encouraging style of Andrew Ng

por Carlo A A D A

Jan 23, 2018

Some minor inaccuracies in videos

por Duvan A

Mar 04, 2019

Some videos have edition mistakes