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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

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.

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.

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626 — 650 de 5,576 Avaliações para o Structuring Machine Learning Projects

por Adnan B

28 de dez de 2017

Great course underlining that one should think first and then implement. It also helps to understand where to put the effort when we face real-world AI challenges. Thank you guys, great course!

por Daolong W

19 de nov de 2017

This course was very helpful for me to understand more about building a good deep learning system myself and working with others to build one such system together. Thanks for the good lectures!

por Abel G

11 de set de 2017

I learnt a lot. Keep the good work for the whole team behind the course. Personally to Prof. Andrew Ng, thank you for your easy way of explaining things and achieve what I have achieved so far.

por Roger G

25 de ago de 2017

This course give valuable insights on how to work more efficiently and explains very well some ways to improve decisions when one is part of a team solving a difficult machine learning problem.

por Anna

8 de jan de 2021

Andrew is again great in breaking the course down into easy to understand concepts. I enjoy how he always makes a comment not too worry if we did not understand something from the first try :)

por Bharat S H

30 de mar de 2019

I hope my mentor will live for thousand years. The world needs person like you. I have learnt a lot. Confidence as an machine learning engineer is increasing day by day.Thanks a lot Professor.

por Tejas S S

7 de nov de 2018

Definitely should not overlook this course. It may seem small, but provides the insight needed for major projects. Consider this as precious gems of advice that you should follow like the law!

por Pang C H J

21 de abr de 2021

I have a feeling that other people/ books don't seem to discuss the material in this class that much. But the material in this class might be more important in practice than the other theory.

por Thomas N

7 de mar de 2019

This give you guidelines how to approach a machine learning problem. You will get experiences from the tutors instead of struggling years to find out what should have done in the first place.

por Marc v W

28 de nov de 2018

This course teaches a good amount of practical skills which can help approach a problem in a way that can save a lot time. I wasn't expecting something that useful and complete. Great course.

por Luigi S

21 de mai de 2018

This course may seem less technical than the others but it provides a lot of best practices that will impact your work probably more than what you have learnt from the more technical courses.

por Heyang W

19 de ago de 2017

This one is especially helpful since it contain first hand tuning guide line towards different settings of DL scenario. The case study in homework reinforce what Andrew taught on the lecture.

por Samrat S

14 de ago de 2017

Very insightful, its clear Andrew is sharing his personal experience with the live projects here. As i also feel i am doing lots of things similar in real life projects.. Great work Andrew Ng

por Philip L

14 de mai de 2019

Great course. It help me learn about what should be the next step to take for our deep learning projects. We should have more strategic courses like this not only online, but also at school.

por Jae-Hong M

4 de nov de 2018

Good approach to how to tackle machine learning problems to increase the efficiency and accuracy of implementation. Gives a lot of tips and tricks that are not usually noted in ML textbooks

por Daniel D

29 de ago de 2018

I love the way Andrew goes beyond teaching the foundations of a technology and launches into how to plan projects well for success. This course was, like the others, very much worth taking.

por Gopikrishnan M

11 de dez de 2017

This course tells us how to approach a machine learning project. This is very useful, especially from a beginner's perspective, since a project with huge amounts of data can be pretty scary.

por Alexis C O

3 de mai de 2020

Such a great course, add more content to this course, this is very helpfull to people who never has worked in a machine learning project and also to people little experiencied in this field

por grzegorz k

4 de mar de 2020

More theory and thinking about potential projects. Happy this was added into specialization because on my own I wouldn't bother spending too much time on this stuff which is very important.

por Prashant S

14 de fev de 2019

Excellent course!! I had done a few AI projects in college, nothing professionally. This course is excellent. Really makes you understand how to deal with data sets in real world projects.

por Dengrong J

25 de set de 2018

This course teaches you a lot of strategies in machine learning, which potentially can save a lot of time when developing machine learning products as it helps you find the right direction!

por Bernardo H

1 de jul de 2018

Concise classes, with good examples of different situations. It teaches us how to get insight from the results of our project, finding the point where the team should focus its effort next.

por Tulsi J

16 de mar de 2018

This course is really awesome. I feel the same problem this project addresses. When projects get bigger, it becomes really difficult to handle them. And this course guide you to solve this.

por Ferenc F P

8 de mar de 2018

This course is focused more on practical advices in order to avoid pitfalls when solving real problems. As Prof. Andrew Ng. highlighted in most courses these hints are not discussed at all.

por Rui W

25 de ago de 2017

even without the coding project, I think the big pictures will help me in the future. I definitely will rewatch the guidelines many times!

Again, thanks for your insights and instructions!!!