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

4.8
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47,322 classificações
5,432 avaliações

Sobre o curso

In the third course of the Deep Learning Specialization, you will learn how to build a successful machine learning project and get to practice decision-making as a machine learning project leader. By the end, you will be able to diagnose errors in a machine learning system; prioritize strategies for reducing errors; understand complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance; and apply end-to-end learning, transfer learning, and multi-task learning. This is also a standalone course for learners who have basic machine learning knowledge. This course draws on Andrew Ng’s experience building and shipping many deep learning products. If you aspire to become a technical leader who can set the direction for an AI team, this course provides the "industry experience" that you might otherwise get only after years of ML work experience. The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI....

Melhores avaliações

AM
22 de Nov de 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.

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.

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4501 — 4525 de 5,392 Avaliações para o Structuring Machine Learning Projects

por Uddhav D

2 de Jun de 2019

I feel more Examples should be given regarding the variable and bais tuning, also Error analysis videos should be a bit in-depth. Everything else is as good as it can get :)

por Jean M A S

27 de Out de 2017

The simulations were very good to build a good intuition about setting up a machine learning project.

But I regret that we didn't have coding exercises. 4 stars for this one.

por Carlos S C V

15 de Abr de 2020

Me gustó el curso, pero creo que algunas lecciones fueron un poco más largas de lo necesario. Debo agregar que me gustaron mucho los simuladores, creo que me ayudaron mucho

por Vinod S

19 de Nov de 2017

Helps clearly in understanding practical aspects of deep learning. An additional week, highlighting the aspects of productionizing a deep learning project would have helped

por Vinay N

12 de Jul de 2020

Since I myself am working on a few projects, the concepts here are somewhat useful in error reduction. Especially when the models are used to automate medical applications

por Palathingal F

28 de Set de 2017

A unique course to understand the process of establishing a ML project. But lacks tools information and a more structured definition of the process. A bit too theoretical.

por Mahnaz A K

2 de Jul de 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 Vivek V A

13 de Fev de 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 Ivan L

25 de Jun de 2019

Most of the material was quite useful, but some was, perhaps, too obvious. Also, some things were discussed too thoroughly, and, in my opinion, that was a waste of time.

por Алексей А

14 de Set de 2017

Would be great to obtain more concrete information.

For example, instead of "requires much more training data" to obtain "requires ~1'000'000 samples instead of ~100'000"

por Rafal S

22 de Jul de 2019

Excellent content overall. However, reiterates some of the knowledge already presented in the two previous courses of the specialization. Lacks programming assignments.

por Amir R K P

7 de Dez de 2018

I wish there was more examples, visualization and depiction of work with referral to papers or experiment here. or perhaps a bit of project management, data management.

por Pete C

24 de Jun de 2018

Enjoyable, but felt a little less challenging and more hastily assembled. Regardless, the material is valuable and as always, a pleasure to be instructed by Andrew Ng.

por Lars R

29 de Ago de 2017

The course material is relevant and useful, however, I agree with other reviewers that these 2 weeks should rather be a 1-2 weeks addition to one of the other courses.

por Andrew R

30 de Abr de 2018

Quick course. Worth taking because gives some practical guidance on what avenues to pursue when finding a optimal model (which takes into account human time required)

por Poorya F

10 de Dez de 2017

The first week is too long with repetitive materials. The second week is very interesting. However, I wish the course was designed such that it required some coding.

por Hany T

27 de Ago de 2019

Great course, great professor .. the only issue is that I feel sleepy every time I watch the videos :), it's some how single tone. Also the audio could be improved.

por Karthikeyan C (

16 de Mar de 2020

It is always important to learn above the problem-solving methods and tools. This course teaches the complete diagnosis methodologies for Machine Learning problems

por Mehran M

25 de Jun de 2018

Overall, very informative, however I think the content of this course could be divided between the first and the second course.More assignments would've been nice.

por Rajesh R

26 de Nov de 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 Ross K

30 de Ago de 2017

Useful introduction to meta-level principles of machine learning process management, but not quite as groundbreaking or well-instructed as the previous two courses

por kArThIk T

13 de Abr de 2020

A real time project or programming assignment could improve our confidence level.

All of these courses if it had readable material along with video, it'd be great.

por SYZ

9 de Dez de 2018

Hope to have coding practices for the second week's materials.

Anyway, the current course is already very helpful. Thanks to Andrew and all staff behind the scene!

por Jussi V

18 de Fev de 2018

Content is good, but a bit thin... This course makes sense as part of the deep learning specialisation, even if this is a bit too short to be a course of its own.

por Boris D

23 de Jul de 2019

A bit less interesting than the others I think. To me the whole first week was full of obvious stuff. The second week, however, was very interesting and helpful.