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

31,345 classificações
3,292 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


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.


Mar 08, 2018

Going beyond the technical details, this part of the course goes into the high level view on how to direct your efforts in a ML project. Really enjoyable and useful. Thanks for making this available!

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151 — 175 de {totalReviews} Avaliações para o Structuring Machine Learning Projects

por Bạch T T

Mar 03, 2019

it's good. but hard

por Hanna P

Mar 02, 2019

A helpful course. It would be nice to review some parts of ML projects even in more details as there are so much places where an ML engineer can be unsure.

por Camilo G

Mar 03, 2019

A great summary of tactics to improve Deep Learning practices, I will continue to look through this videos to see if I continue to apply the practices in the future

por Mallikarjun C

Mar 01, 2019

Excellent course

por Seth L

Mar 25, 2019

Andrew Ng is such a great teacher, it is a pleasure to learn machine learning and deep learning from his well thought-out lectures and examples


Mar 25, 2019

A practical course!!

por Ashok R A

Mar 27, 2019

Good Course

por Duong V T

Mar 26, 2019

It is very intuitive and will help to accelerate the development progress in real project

por Kelvin G

Mar 28, 2019

Andrew NG impressive. As always

por Sergio L M

Mar 28, 2019


por Marilson C

Mar 28, 2019

Great course.

por Zigmond V L

Mar 29, 2019

Good, practical information to help tackle ML projects most effectively.

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 Charles Z

Mar 29, 2019

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

por Lucifer Z

Mar 30, 2019


por Bharat S H

Mar 30, 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 Mathew S

Mar 29, 2019

Excellent high level discussions. I am thankful I completed this course before getting too deep into my current deep learning 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.

por 谢凯源

Mar 31, 2019


por RAJ S

Mar 31, 2019

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

por Vatsal D

Mar 19, 2019

nice course

por Sergei S

Apr 01, 2019

Among other courses of this series, this course brings up some of the most important things every (deep learning) scientist should be aware of.

por Kartik g

Apr 01, 2019

Its quite informative

por xuezhibo

Jan 28, 2019

very good!

por 罗家伟

Jan 29, 2019