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

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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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551 — 575 de 5,522 Avaliações para o Structuring Machine Learning Projects

por Guilherme

5 de dez de 2017

The discussions on practical guides about designing deep learning systems, dealing with data, bias variance trade-off, and how to organize projects to optimize time usage are much needed for practitioners.

por Terrence G

12 de out de 2017

Practical advice for new students when tackling a real-world ML project and how to approach to optimize a model's performance. The quizzes provide good examples of use-case scenarios and decisions to take.

por Juan P A C

23 de set de 2020

I think the simulations were great. They give an excellent approach to real life enterprise scenarios where you have to take important decisions. Great compliment for the first two courses of the program.

por Harshal R P

31 de mai de 2020

Step by Step approach to structure Your Machine leaning project from scratch. The cherry on the cake is simulation quit provided at the end, helps quite fast to get the practical approach to the problems.

por Anurag C

5 de dez de 2019

This course is very helpful to fine tune our machine learning and our deep learning projects and probably more input to the different types of transfer learning examples could have been much more helpful

por Mustafa A

1 de dez de 2019

I love it. it was very helpful but I think if it was an assignment "programming assignment" with some issues "mismatch, incorrect labeling, .. etc " and use those techniques it would be much more helpful.

por Mohamad K

2 de dez de 2018

Its most great and important course ever, please try to listen very carefully to Prof Andrew, he tell you about each and everything you need to become master in ML. Many thanx for Prof Andrew and COURSERA

por Sudip B

4 de dez de 2020

I really enjoyed taking this course. The use cases and practical strategies to the problems were really insightful. I'm really excited to apply what I learnt from this course on my own personal projects.

por Romayssa B

10 de set de 2020

I learned a lot of new methods to structure not only deep learning projects but also ML projects. Very interesting and gives a wide overview of how we can improve our project management in AI in general.

por Frantisek H

4 de set de 2020

Excellent course - Andrew's teaching is what's so needed in the machine learning community. He explains concepts properly so that one truly understands them, and thus knows what to do when applying them.

por Islam W

7 de jun de 2020

Prepare you for the problems faced in machine learning projects, I'm now capable of analyzing projects for other people although I'm only in the path of Machine learning for 40 days.

Thank you, Sir Andrew

por Muzammil

18 de mai de 2019

I believe Andrew Ng shared some key insights into building successful machine learning projects. I really enjoyed the course and believe the shared information to be invalueable for my further research.

por Rajesh C

15 de out de 2018

This is the most important course of all the machine learning courses from deeplearning.ai. I learned in two weeks, what normally will take years of experience from this course i.e. ML project strategy.

por Aleksandar S

5 de fev de 2021

Well structured course for structuring machine learning projects. I've looking forward to go more with similar learnings. It is very helpful to expand an idea. Shortcuts with projects are promised here.

por Patrick F

25 de jun de 2020

That course is so valuable in order to drive into a ML project. Especially, the project life-cycle simulator are really awesome to practice model diagnostic and what to do next !! Really amazing module!

por Rohan S

17 de abr de 2020

A very unique and practical-based course that really shows the intricacies involved in making a machine-learning project and Andrew has really provided with hardcore lessons from his enormous experience

por Govinda N D

30 de out de 2019

Course is really useful in explaining which part to focus on to reduce the error and how to detect which part of algorithm should be given more time to reduce error and improve performance of algorithm.

por peter b

3 de set de 2019

A bit more theoretical this time. But the information is worht the time. I think that the knowledge Andrew is spreading will make me more efficient in my AI jobs ahead. At least I hope and think that :)

por Craig M

6 de dez de 2017

Andrew Ng's excellent teaching style leaves you with an intuitive understanding of machine learning setups and potential pitfalls. For me it's the best way to learn; this stuff really sticks in my head!

por Esteban J R

23 de abr de 2021

Incredible course, so full of practical advice from Andrew Ng. Ah, and speaking about transfer learning, I cannot stop surprising myself of Andrew's ability to transfer his learning from him to others.

por Gaetan P

12 de jun de 2020

Very well structured course about all the little tuning things to be done to actually make a machine learning algorithm work well. It is really a course to be taking as part of an overall ML formation.

por Wilem

24 de nov de 2019

Really interesting!

We used to be concerned about unbalanced train/dev/test, and with this course I realised this are not the main problems for achieving performance in ML

A master class.

Thanks Andrew!

por William G

14 de jul de 2019

not as technical as the first 2 courses in this specialization (and the next 2 for that matter), but it is still a well rounded course and highly recommend to do all the courses in this specialization!

por Karthik V

11 de set de 2018

Extremely interesting and useful practical advice that can help make significant difference when thinking about how to identify and correct problems. The quizzes were fantastic and made me think a lot.

por Ernesto N S

4 de dez de 2017

Excellent material. I would say this is the most important course of this specialization. Knowing how to approach a certain problem can indeed save us a lot of time and help us avoid a lot of mistakes.