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Structuring Machine Learning Projects(으)로 돌아가기

deeplearning.ai의 Structuring Machine Learning Projects 학습자 리뷰 및 피드백

30,506개의 평가
3,209개의 리뷰

강좌 소개

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....

최상위 리뷰


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 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.

필터링 기준:

Structuring Machine Learning Projects의 3,175개 리뷰 중 151~175

교육 기관: Bạch T T

Mar 03, 2019

it's good. but hard

교육 기관: 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.

교육 기관: 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

교육 기관: Mallikarjun C

Mar 01, 2019

Excellent course

교육 기관: 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

교육 기관: MOUCI

Mar 25, 2019

A practical course!!

교육 기관: Ashok R A

Mar 27, 2019

Good Course

교육 기관: Duong V T

Mar 26, 2019

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

교육 기관: Kelvin G

Mar 28, 2019

Andrew NG impressive. As always

교육 기관: Sergio L M

Mar 28, 2019


교육 기관: Marilson C

Mar 28, 2019

Great course.

교육 기관: Zigmond V L

Mar 29, 2019

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

교육 기관: 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

교육 기관: Charles Z

Mar 29, 2019

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

교육 기관: Lucifer Z

Mar 30, 2019


교육 기관: 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.

교육 기관: 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.

교육 기관: 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.

교육 기관: 谢凯源

Mar 31, 2019


교육 기관: RAJ S

Mar 31, 2019

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

교육 기관: Vatsal D

Mar 19, 2019

nice course

교육 기관: 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.

교육 기관: Kartik g

Apr 01, 2019

Its quite informative

교육 기관: xuezhibo

Jan 28, 2019

very good!

교육 기관: 罗家伟

Jan 29, 2019