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

48,226 classificações
5,532 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


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.


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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2726 — 2750 de 5,500 Avaliações para o Structuring Machine Learning Projects


13 de abr de 2020

Great advice for working on practical ML projects.

por Alexandre F

21 de jan de 2020

useful insights into how to deal with a DL problem

por Dmytro P

8 de out de 2019

Great insights from the industry for the beginners

por Michael C

4 de jul de 2019

Another excellent course that I enjoyed immensely.

por Pedro R

25 de jun de 2019

Very good content quality and challenging quizzes.

por Rich T

27 de mai de 2019

Really a good overview for how to manage a project

por Tati H

3 de fev de 2019

well designed and taught! thank you good people!!!

por Sanjeev U P

23 de abr de 2018

Good practical advice on how to approach projects.

por Stephen W

17 de fev de 2018

great as all other course in this specialization !

por Zamirbek A

18 de jan de 2018

very helpful insights. loved the ML pilot projects

por Xingtong L

14 de jan de 2018

This is one of the best courses I have ever taken!

por Desigan P

13 de dez de 2017

Pearls of wisdom in this course. Excellent course!

por Ling L

11 de nov de 2017

great info, can apple to other ML project as well.

por Salvador N G

3 de nov de 2017

The simulations were very useful, good job Andrew.

por Jianhui H

11 de dez de 2020

lots of great practical advise, really good stuff

por Thaha M T

15 de out de 2020

very helpful to practical implementation of ideas

por Pablo I

10 de jun de 2020

Muy agradecido por los Tip que dan en este curso.

por Anis b Y

21 de mai de 2020

very easy to understand the intuitive explanation

por John T S

4 de abr de 2020

The course is extremely well guided and narrated.

por Thomas P

1 de abr de 2020

Very useful and valuable tips from a true expert!

por Evan D

23 de mar de 2020

Super helpful practical knowledge for ML Projects

por Kalyan P

9 de fev de 2020

A must course for every machine learning engineer

por Anna A

29 de dez de 2019

Extremely useful; key concepts clearly explained.

por Alternate R

17 de nov de 2019

Super helpful course for any DL/ ML practitioner.

por Zaman M

4 de out de 2019

I have learnt a lot about ML project structuring.