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Structuring Machine Learning Projects(으)로 돌아가기

deeplearning.ai의 Structuring Machine Learning Projects 학습자 리뷰 및 피드백

4.8
별점
42,305개의 평가
4,750개의 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

JB

Jul 02, 2020

While the information from this course was awesome I would've liked some hand on projects to get the information running. Nonetheless, the two simulation task were the best (more would've been neat!).

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.

필터링 기준:

Structuring Machine Learning Projects의 4,704개 리뷰 중 4251~4275

교육 기관: Mage K

Mar 07, 2018

Would've liked to have some programming assignments

교육 기관: Carlisle

Aug 20, 2017

Introduced a lot on engineering project experiences

교육 기관: Marcelo A H

May 29, 2020

Very interesting topics were shown in this course.

교육 기관: William L

Apr 17, 2020

Very useful knowledge that is not commonly taught.

교육 기관: Alvaro G d P

Nov 27, 2017

Interesting but perhaps we could have gone deeper.

교육 기관: John H

Aug 26, 2017

Is the flight simulator hw going to be added soon?

교육 기관: Pat B

Dec 08, 2019

Great course. I liked the compact, 2-week format.

교육 기관: liu c

Mar 17, 2018

A little bit abstract. But still very inspiring!

교육 기관: Florian M

Aug 24, 2017

Very interesting tools and ideas for applied ML.

교육 기관: Jason G

Nov 25, 2018

Not as strong as the other 4 of 5 of the series

교육 기관: Mark

Oct 13, 2018

Great course. Needs deeper practical examples.

교육 기관: Francis J

Feb 25, 2018

A lot of insights rather than technical details

교육 기관: Lukáš L

Jan 07, 2018

Coding exercises would be great in this course.

교육 기관: Tulip T

Jul 23, 2019

Quite helpful when you start a new ML project.

교육 기관: S V R

Nov 05, 2018

The session were simple, could be more complex

교육 기관: Caique D S C

Jul 31, 2018

very good course, could be less massive though

교육 기관: Виницкий И В

Dec 11, 2019

I want a program exercise like in 1-2 courses

교육 기관: Dionysios S

Nov 30, 2018

I would like to see more practice assessments

교육 기관: Luis E R

Jul 31, 2019

Very useful concepts that few people address

교육 기관: Jun P

Apr 22, 2018

Kind of boring than the cnn and rnn class ..

교육 기관: John H

Aug 29, 2017

Useful content, could be much more succinct.

교육 기관: vijaykumar

May 15, 2020

This course is awesome and good knowledge .

교육 기관: Alfredo M

Mar 14, 2018

There were no practical coding homeworks :(

교육 기관: Igor C C

Feb 14, 2018

A little less dense than the other courses.

교육 기관: Rajesh M

Oct 11, 2017

Can reduce some of the repetitive material