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Voltar para Structuring Machine Learning Projects

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

4.8
stars
34,748 classificações
3,631 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.

WG

Mar 19, 2019

Though it might not seem imminently useful, the course notes I've referred back to the most come from this class. This course is could be summarized as a machine learning master giving useful advice.

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3401 — 3425 de {totalReviews} Avaliações para o Structuring Machine Learning Projects

por Vincent P

Aug 24, 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 Leitner C S E S

Sep 15, 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

Oct 14, 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

Jan 30, 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

Nov 16, 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 Jordon B

Feb 01, 2018

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

por ccbttn

Oct 12, 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

Jan 28, 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

Sep 25, 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

Oct 20, 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 Rindra R

Oct 11, 2017

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

por Eric K

Jul 21, 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

Oct 20, 2017

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

por Bongsang K

May 21, 2018

I think this lecture is important for every research scientist. However, there was no programming examples so I was confused sometimes.

por Michael L

May 02, 2018

No programming assignments or labs, so too much theory, and too little chance to put same into practice. Not a good value for my money.

por Max S

Dec 13, 2017

Still good but getting much sloppier. Bad editing of the videos, some exercises plain wrong and staff not reacting to forum posts, etc.

por Lars L

Dec 30, 2017

Course materials need some cleanup. Were a number of audio blips, in the video. Material was good but just didn't seem as polished.

por Taavi K

Nov 30, 2017

Too short on its own (took half a day to go through the whole thing), could have been combined with Course 2 of the specialization.

por sai r t

Aug 06, 2018

this session was good it would be more better if they provided the code of them..so that we could be abke to learn more from them

por Dennis G

Nov 24, 2017

Felt a bit rushed, each video was full of good tips but personally I think each video should have been a jupyternotebook instead.

por Massimo A

Nov 18, 2017

More theoretical than the other courses in the specialisation but still very high quality.

Short but with a lot of information.

por David P

Oct 17, 2017

Not nearly as good as the first two courses. These two weeks should probably be added into the second course at some point...

por Oliver O

Oct 16, 2017

Would like more applied discussion and for it to be Longer. In particular I would like to see a discussion on class imbalance.

por Shuai W

Sep 19, 2017

The content of this course is a bit too little for me.

However, it provides useful guidance for my projects. Much appreciated!

por Gary S

Sep 16, 2017

Not nearly as valuable as the first Deep Learning course. And the questions posed in the quizzes seemed far more subjective.