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

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47,534 classificações
5,451 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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476 — 500 de 5,412 Avaliações para o Structuring Machine Learning Projects

por Aloysius F

20 de Mar de 2020

Excellent, this really goes into the nuance of successfully executing a project. Setting up an initial system is not that difficult. Understanding the sources of error a systematically resolving requires judgment and graft.

por amin s

26 de Jul de 2019

This course is great. Recommend it to anyone working on Deep Learning projects. Saved me lots of time, and taught me how to systematically think about my problem and opened new windows to improve my network. Thanks, Andrew!

por Sean C

15 de Fev de 2018

This was a valuable stepping stone in applying Andrew Ng's other teachings to realistic scenarios. The "simulators" were actually a great representation of realistic machine learning project issues & potential resolutions.

por Kurt K

27 de Nov de 2017

A clear explanation of a difficult subject with an emphasis on being able to create and to understand your own neural networks.- Plus in this module how to allocate your resources so you can achieve a successful project.

por Asad A

2 de Set de 2019

Really good insights into the practical aspects of structuring projects. Large scale deep learning/ ML is as much about people management and strategic prioritization as it is about complex algorithms and big data handling

por 邱依强

10 de Mar de 2018

This is a very useful course since that you can get an impotant instruction to build your own project. You can reduce your time cost and iterate quickly to produce more value by using the knowladges taught by this course.

por arulvenugopal

8 de Jan de 2018

Good. However, understanding the importance of strategy, either additional scenario quiz (the simulation type quiz is good) or a programming assignment would reinforce the understanding (given short duration of the course)

por Heidi V B

17 de Mai de 2020

I loved the translation of all the different succesfactors to the daily practice and examples in the course. It gave me an general idea of what to look out for when identifying my own AI problems and defining a NN for it.

por Abhishek R

15 de Set de 2019

This was probably the most useful course of the entire specialization with real-world examples, tips, tricks and techniques on how to approach the problems in Machine Learning world as a whole and Deep Learning in general

por Francisco R

28 de Set de 2017

Even though it's a short course and it doesn't have programming assignments, which I love doing, it has though these case study, which are quite fun and educative, helping you to get started in a Machine Learning project.

por Andrés S

24 de Mai de 2020

I liked this course because I gave me an idea of real situations I could face working on Machine Learning, but I think a little code would've been helpful, for example, to better understand how to do a transfer knowledge

por Ladislav Š

20 de Out de 2019

This part of Deep learning specialization is similar to Machine Learning Yearning written by prof. Andrew Ng. I read the whole book and for me this was mostly a repetitive information - however, very useful and relevant.

por Shishir V

23 de Nov de 2020

a lot of value for the minimal time invested, and the case study approach was the main reason I would give it 5 stars. Some parts in the videos could be fleshed out more with more real world examples where it was vauge.

por Naresh K P

25 de Jul de 2020

This course helped me understand how to prioritize problems that we encounter in Machine Learning space. On the surface this might look simple, but I think this course will have a huge impact as I implement ML problems.

por TANVEER M

18 de Ago de 2019

The course taught me about errors how to minimise the errors .How we can improve model performance.satisficing and optimising metrics.Overall the course was quite good.The case studies I found more interesting to solve.

por Akshat A

16 de Mai de 2020

Amazing Course! I generally don't feel like I gain much from lectures and would prefer reading but I'm really glad I took this course, gave me lots of insights into how one would go about improving performance quickly.

por Madalena R

20 de Nov de 2019

I really enjoyed this course, I think Andrew has a lot of knowledge on the subject matter and he is able to explain it in a very detailed and understandable manner. The interviews were a plus and also very interesting!

por Bedirhan Ç

24 de Jul de 2020

Videos were really help me understand the decision making and strategies for machine learning projects and quizzes were quite good real life simulations of what decisions i could make. I learnt a lor from this course.

por Utsav A

24 de Abr de 2020

This case was useful for getting an experienced way of approaching the real-world problems of ML. The quizzes further added to the application of the basics learnt throughout the course. Overall, it was a good course!

por 谢宁翔

8 de Abr de 2020

very much wonderful. especially the simulation process, which extracts the pure logic decision process during implementing DNN without actually experiencing all the detailed procedures which are not really challenging

por Lewis C

27 de Jan de 2020

Good course. Very interesting!

Having done the course, most of the ideas seem fairly obvious. However, the chances of me coming up with them on my own are almost 0.

Therefore I think the training has been successful.

por Muhammad S K

1 de Ago de 2019

It was an amazing experience and I learn a lot of new Machine Learning strategies and error analysis techniques that will help me a lot in my future research work. Thanks a lot, Mr. Andrew, you are an awesome speaker.

por Luiz A N J

28 de Dez de 2018

Excellent course, give great practical advice of how to structure projects and to make decisions to improve you models. Those insights are hard to find elsewhere and it's the most valuable contribution of this course.

por Guillermo A M G

29 de Out de 2020

I found very useful this course. It is different of what you'll find anywhere because of its focusing in the strategies for developing deep learning projects. Andrew share his experience in a short but unique course.

por Md. S R

21 de Jul de 2020

I really loved the learning of different ways of error analysis and solving issues based on the outcomes of the analysis. This is really a ready to use knowledge for me to implement in my job life. Thank you so much!