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

4.8
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44,741 classificações
5,070 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

TG
29 de Nov 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.

JB
1 de Jul de 2020

While the information from this course was awesome I would've liked some hand on projects to get the information running. Nonetheless, the two simulation task were the best (more would've been neat!).

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4776 — 4800 de 5,014 Avaliações para o Structuring Machine Learning Projects

por Jose P

30 de Set de 2019

Topics are a bit vague, which is fine as the content is interesting and useful nonetheless, but perhaps exposition is too lengthy relative to the amount of content.

por Robbin R

17 de Fev de 2018

Gives good insights on how to work on a Machine Learning project yet. Provides some rule of thumbs for different hick-ups that may be encountered during a project.

por Nick S

8 de Set de 2017

even though there are great tips and advices, it does not justify an entire course and they can be mentioned in 3 videos so a lot of the videos were repetitive.

por Kan X

18 de Fev de 2020

I like this specialization in general. However, this third one has too many overlapping contents and some videos are not that useful. Just personal opinion.

por Jkernec

23 de Dez de 2017

Homework is lacking. It is too easy to pass. I feel like the programming task or homework task fell short. The lectures were good but too little practice.

por Hanbo L

22 de Set de 2019

Good non-technical materials, but short enough to be incorporated into other courses. Some aspects feel subjective. Many typos/minor mistakes in quizzes

por Vincent P

24 de Ago de 2019

Was really enthousiastic about the first two courses in the specialization, the third however felt a bit like going back a step in level of advancement.

por Rishabh G

22 de Mai de 2020

A different course for only two weeks of content? This is nuts. I waited for 15 days for financial aid to be approved and I completed it within 5 days.

por Leitner C S E S

15 de Set de 2017

Only interesting if you don't have much experience with machine learning; Might or might not be great if you are a novice, though - hard to say for me.

por Deleted A

14 de Out de 2017

There was some very valuable material. However, I think some of the videos could have been prepared a little bit better and could do with more editing

por Carsten F

30 de Jan de 2018

Course was less interesting than the other parts. Also very negative that the last part of the 5-part specialization is taking ages to be finalized.

por Dany J

15 de Nov de 2017

Good content, but could definitely benefit from a more fleshed out problem to solve. The content beg for a larger concrete coding exercice project.

por Hugo J

2 de Nov de 2020

It's easy and more simple than the others in specialization. Can be more deeper into ML project organization management. It's ok, could be better!

por Jordon B

31 de Jan de 2018

This course did not contain programming assignments, only quizzes, and was thus considerably less useful, even though the knowledge was important.

por ccbttn

12 de Out de 2017

Quite some questions are confusing and some are not correct itself. and this course is more concept based, didn't actually get to program a lot.

por Giacomo A

28 de Jan de 2018

Contains some useful tips, but they are a bit too diluted - I feel like it could have lasted much less and still conveyed the same information.

por Yancey S

25 de Set de 2018

This course provides some interesting insights into how to approach machine learning projects, but feels a little light on substance at times.

por Even G

20 de Out de 2017

Great content. Some strange audio that I think should've been cut (especially in week 2). I suspect the week 2 quiz is a little buggy as well.

por Mayur S

25 de Mai de 2020

The course material can be clubbed with existing courses. It would have been much more meaningful with some examples and hands-on assignments

por Rindra R

11 de Out de 2017

Covered important topics and real-world project considerations. However, the content and assignments are too short to make it a full course.

por Daniel K

25 de Jun de 2020

This time it was not that well-structured than the previous courses. I thought we would learn how to structure step by step an ML project.

por José G

18 de Abr de 2020

Lots of information, few knowledge

Change name to "Struc. Deep Learning Projects", all other forms of ML not considered, specially for P2.

por Eric K

21 de Jul de 2018

Too much similar material to the prior course, and only two simple quizzes, no hands-on programming assignments like in earlier courses.

por Eric M

20 de Out de 2017

A fundamentally very good course with a few technical gltiches that can be easily corrected and some confusing elements to be clarified.