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

4.8
estrelas
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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4526 — 4550 de 5,014 Avaliações para o Structuring Machine Learning Projects

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

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

por Carlisle

20 de Ago de 2017

Introduced a lot on engineering project experiences

por Marcelo A H

29 de Mai de 2020

Very interesting topics were shown in this course.

por William L

17 de Abr de 2020

Very useful knowledge that is not commonly taught.

por Alvaro G d P

27 de Nov de 2017

Interesting but perhaps we could have gone deeper.

por John H

26 de Ago de 2017

Is the flight simulator hw going to be added soon?

por Pat B

8 de Dez de 2019

Great course. I liked the compact, 2-week format.

por liu c

17 de Mar de 2018

A little bit abstract. But still very inspiring!

por Florian M

24 de Ago de 2017

Very interesting tools and ideas for applied ML.

por Jason G

24 de Nov de 2018

Not as strong as the other 4 of 5 of the series

por Mark

12 de Out de 2018

Great course. Needs deeper practical examples.

por Francis J

25 de Fev de 2018

A lot of insights rather than technical details