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Comentários e feedback de alunos de Structuring Machine Learning Projects da instituição

45,329 classificações
5,162 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

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!).

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.

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4601 — 4625 de 5,107 Avaliações para o Structuring Machine Learning Projects

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 Hanqiu D

9 de Jan de 2021

It's too easy and cannot be a reasonable single course.

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


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


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.


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

por Ktawut T

10 de Out de 2017

Very useful materials for leading a ML research team

por awalin s

29 de Set de 2017

interesting insights about real world implementation

por Yu L

3 de Abr de 2020

would like to have more excercise related to coding

por Mage K

7 de Mar de 2018

Would've liked to have some programming assignments