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

4.8
estrelas
44,660 classificações
5,057 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

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!).

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 5,003 Avaliações para o Structuring Machine Learning Projects

por Joseph C

9 de Abr de 2018

Needs programming exercises to help firm up the new ideas.

por QUINTANA-AMATE, S

20 de Mar de 2018

Completely new of what it is out there. Well done Andrew!!

por Alejandro R V

8 de Jan de 2018

Not as interesting as the others, I personally prefer math

por Gopala V

24 de Out de 2017

Gave some ideas on mismatched data and how to address them

por Akshita J

23 de Abr de 2020

An assignment could have been included to let practically

por Roberto J

19 de Out de 2017

A bit dry, would love to see some more concrete examples.

por Vinicius B F

22 de Out de 2017

Content was fantastic, but the videos were badly edited.

por Suresh P I

10 de Set de 2017

Can be potentially folded into other courses if possible

por heykel

27 de Jan de 2020

very helpful to build an intuition for DL strategies...

por Rafael G M

7 de Dez de 2019

Providing further references would benefit this section

por WEIJIAN K

15 de Nov de 2017

You can know well a lot of strategy in machine learning

por B S K

14 de Jul de 2020

Good teaching of practical approaches and nice quizzes

por 王毅

24 de Dez de 2019

the content is good, but the videos are not well made.

por Shuochen Z

17 de Fev de 2019

内容架构很好,讲得也很实用,但觉得课时有些短,许多重要且有趣的问题都未能得到展开详述。期待后续的扩充课程~~

por Gundreddy L M

11 de Set de 2018

excerice should be given for this one proper user case

por Alexey S

22 de Out de 2017

Good class, but 2 previous are much better and useful.

por Lei C

25 de Set de 2017

the answer of the assignment is a little bit arguable.

por SANJAY P

6 de Out de 2020

Content is good. Presentation could have been better.

por Kumari P

28 de Mai de 2020

machine learning project are highly iterative as you.

por diego s

18 de Fev de 2020

I miss notebooks for practice, besides questionnaires

por Xinghua J

6 de Set de 2019

If there is some coding practice, it would be better

por Pranjal V

11 de Jul de 2020

Very well explained but needs more reading material.

por Hee s K

18 de Abr de 2018

It is an unique lecture providing empirical advises.

por Pablo L

30 de Out de 2017

Great set of guidelines. Mostly theoretical, though.

por Cristina G F

22 de Out de 2017

Concrete reminders of important and practical points