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

4.8
32,911 classificações
3,466 avaliações

Sobre o curso

You will learn how to build a successful machine learning project. If you aspire to be a technical leader in AI, and know how to set direction for your team's work, this course will show you how. Much of this content has never been taught elsewhere, and is drawn from my experience building and shipping many deep learning products. This course also has two "flight simulators" that let you practice decision-making as a machine learning project leader. This provides "industry experience" that you might otherwise get only after years of ML work experience. After 2 weeks, you will: - Understand how to diagnose errors in a machine learning system, and - Be able to prioritize the most promising directions for reducing error - Understand complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance - Know how to apply end-to-end learning, transfer learning, and multi-task learning I've seen teams waste months or years through not understanding the principles taught in this course. I hope this two week course will save you months of time. This is a standalone course, and you can take this so long as you have basic machine learning knowledge. This is the third course in the Deep Learning Specialization....

Melhores avaliações

AM

Nov 23, 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.

WG

Mar 19, 2019

Though it might not seem imminently useful, the course notes I've referred back to the most come from this class. This course is could be summarized as a machine learning master giving useful advice.

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226 — 250 de {totalReviews} Avaliações para o Structuring Machine Learning Projects

por 朱荣鑫

Dec 23, 2018

as good as before

por Pedro M H V

Dec 06, 2018

Good compilation of tricks to improve efficiency when developing, training and testing your deep learning projects.

por Babu V

Dec 24, 2018

Thanks Andrew :)

por Wadikur R

Dec 25, 2018

This course so essential and I learned a lot.

por Lakshya G

Dec 25, 2018

I used to have a lot of related doubts and because of this course I've been able to think them through myself. Thanks a lot, cheers! :)

por Sunji

Dec 25, 2018

Very practical!

por Barbara T

Dec 25, 2018

This class was well worth the time if you've already invested some effort in learning different principles of machine learning. It causes you to reflect back on different implementations, and understand better how to set up a potential problem and determine how to improve it. The many examples helped solidify items in lectures from prior courses in my mind.

por Madhukar R

Dec 08, 2018

Helped a lot to understand the project structuring as professional's perspective

por pravin j

Dec 08, 2018

This was really interesting but at the same time quite tricky to take any decision after we get the poor results. I think it would be even better if we had also programing exercise where we could for example do transfer learning.

por 胡纲

Dec 09, 2018

n内容简介实用,介绍比较清晰

por Avijit K A

Dec 10, 2018

Often it is easy to get lost when fixing/improving your system. Here, it makes things concrete as to which direction to move towards?

por Mahmut K

Dec 10, 2018

Useful course not only for deep learning but for other ML algorithms. Reviews issues that one needs to be careful about using statistical methods.

por Ondrej T

Dec 25, 2018

I really liked the programming assignments in the two previous courses (although, it was usually not enough challenging for me). In this course, I found "case study" assignments very useful and exciting. So far, I am very satisfied with the DeepLearning Specialization; I will definitely continue to the 4th and 5th course. Many thanks for it!

por Patrick L

Dec 26, 2018

helpful a lot to my ML career.

por Deepa K

Dec 26, 2018

great course as usual

por Aleksa G

Dec 26, 2018

More amazing work from Andrew Ng, well done!

por Marcelo F

Nov 27, 2018

Andrew transfers key weights of his pretrained NN on ML Projects to you! Great Value!

por Bhaskar D

Dec 13, 2018

Excellent course. Loved the case study format - good break from the other style of the rest of the courses.

por Zhaiyu C

Dec 28, 2018

empirical lessons, useful.

por 谢凯源

Mar 31, 2019

Nice

por RAJ S

Mar 31, 2019

It was a good idea to place this course in the middle of a neural network flow

por Lucifer Z

Mar 30, 2019

awesome!

por Charles Z

Mar 29, 2019

it's more valuable for troubleshooting of underfitting and overfitting in practice

por TUO W

Mar 29, 2019

It is highly recommended, and you can have a clear and broad-view of how to organize and manage a mature DL project

por Lin Z

Mar 29, 2019

very good guidance on how to start a machine learning project, including many interesting discussions including how to choose the size of training/test/dev set, how to analyze the errors, how to deal with mismatched distributions of test/traning/dev set by adding a training_dev set and how to do end-to-end and multitask training. The contents are well exercised by two well defined case studies.