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

4.8
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45,722 classificações
5,216 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

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.

TG
1 de Dez 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.

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4676 — 4700 de 5,160 Avaliações para o Structuring Machine Learning Projects

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

por Lukáš L

7 de Jan de 2018

Coding exercises would be great in this course.

por Mares B

17 de Nov de 2020

A little short, maybe more hands on exercises?

por Ed G

8 de Nov de 2020

Concise course with some interesting concepts.

por Tulip T

23 de Jul de 2019

Quite helpful when you start a new ML project.

por S V R

4 de Nov de 2018

The session were simple, could be more complex

por Caique D S C

30 de Jul de 2018

very good course, could be less massive though

por Ivan V

11 de Dez de 2019

I want a program exercise like in 1-2 courses

por Dionysios S

30 de Nov de 2018

I would like to see more practice assessments

por Luis E R

31 de Jul de 2019

Very useful concepts that few people address

por Jun P

22 de Abr de 2018

Kind of boring than the cnn and rnn class ..

por John H

29 de Ago de 2017

Useful content, could be much more succinct.

por vijaykumar

15 de Mai de 2020

This course is awesome and good knowledge .

por Alfredo M

14 de Mar de 2018

There were no practical coding homeworks :(

por Igor C C

14 de Fev de 2018

A little less dense than the other courses.