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

4.8
estrelas
47,192 classificações
5,421 avaliações

Sobre o curso

In the third course of the Deep Learning Specialization, you will learn how to build a successful machine learning project and get to practice decision-making as a machine learning project leader. By the end, you will be able to diagnose errors in a machine learning system; prioritize strategies for reducing errors; understand complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance; and apply end-to-end learning, transfer learning, and multi-task learning. This is also a standalone course for learners who have basic machine learning knowledge. This course draws on Andrew Ng’s experience building and shipping many deep learning products. If you aspire to become a technical leader who can set the direction for an AI team, this course provides the "industry experience" that you might otherwise get only after years of ML work experience. The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI....

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!).

AM
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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5026 — 5050 de 5,377 Avaliações para o Structuring Machine Learning Projects

por Yechan K

17 de Jun de 2020

Practical

por IURII B

5 de Abr de 2018

Thank you

por Abhijeet R P

18 de Out de 2017

Great! :)

por 舒意恒

14 de Out de 2017

very nice

por TianPing

27 de Ago de 2017

内容稍稍有点重复。

por Dave

9 de Jul de 2020

verygood

por Yashika S

27 de Set de 2019

good one

por Xiong Z

3 de Set de 2019

helpeful

por Naveen N

28 de Mai de 2019

Awesome!

por mingwei Z

6 de Set de 2018

so well

por 靳雅麟

23 de Dez de 2017

没有中文字幕

por Tất T V

15 de Out de 2017

Useful

por Takuya Kudo

10 de Ago de 2019

Cool.

por Riyaj A

22 de Set de 2017

g

r

e

a

t

por Ansuman B

23 de Mar de 2021

good

por SEUNGMO O

30 de Out de 2020

good

por akash k

13 de Ago de 2020

Good

por Alaa E B

23 de Jun de 2020

good

por CK P D

2 de Mai de 2020

Good

por Annaluru K

17 de Abr de 2020

Well

por VIGNESHKUMAR R

23 de Out de 2019

good

por zhesihuang

3 de Mar de 2019

good

por CARLOS G G

8 de Jul de 2018

good

por Felix E

9 de Out de 2017

This is a 2-week follow-up on the previous two courses in this specialization.

While it's a decent course that goes over a few interesting topics, I have a hard time giving it more than three stars. Reasons for that are below:

(1) Especially the first week felt very slow and repetitive. Most of the material could have been summarized a much smaller timeframe.

(2) The course went over some interesting topics in a very high-level way, but skipped a lot of the details that would have been very interesting to people looking to learn deep learning in depth (like the target audience of this course!).

(3) While I think the approach of having some themed case studies for the test is neat, a lot of the answers left me thinking "well, the correct answer would also depend on X which isn't specified". Good concept to test knowledge in a "discussion/oral exam" session, but IMHO bad for hard "wrong or right" multiple choice tests.

(4) Some videos had "black screen" times at the end, errors, cut-offs and repetitions were not cut out, and overall I think this had the least amount of "polishing" of the courses in this specialization so far.

I'd have preferred if the content of this course were a bit more steamlined and merged it into the other courses of this specialization.

por Aristotelis-Angelos P

6 de Jul de 2018

Overall, I think that it was a good course but in my opinion, the knowledge of this course cannot be easily transferred to people with very few experience in Machine Learning. Therefore, I was wondering whether it should be the 3rd course or the 5th course in this Deep Learning Specialization! Moreover, in order for someone to deeply comprehend these concepts such that he/she is able to apply them in a Machine Learning project, he/she should work on a project on his own where he/she will meet these concepts and will have to search in order to solve them.Last, personally, even though I am quite satisfied from the courses, I would expect that one more course is added to Coursera which is going to require to build a Deep Learning project! I think that this course should be of more advanced level and require (not Intermediate as those ones) and should require from students to build projects like the ones builded in the cs230 class from Stanford.Greetings from a PhD USC student