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Structuring Machine Learning Projects(으)로 돌아가기

deeplearning.ai의 Structuring Machine Learning Projects 학습자 리뷰 및 피드백

4.8
별점
48,329개의 평가
5,551개의 리뷰

강좌 소개

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....

최상위 리뷰

TG

2020년 12월 1일

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.

MG

2020년 3월 30일

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.

필터링 기준:

Structuring Machine Learning Projects의 5,518개 리뷰 중 5476~5500

교육 기관: Alexander V

2018년 2월 25일

A lot of very common-place suggestions that could just as easily be conveyed in a third of the time.

교육 기관: Nahuel S R

2020년 3월 4일

Demasiado contenido teórico sin aplicaciones prácticas reales que permitan consolidar lo aprendido

교육 기관: Peter E

2018년 5월 2일

Too theoretical. It would be good to have some practical (programming) assignments here as well.

교육 기관: Mohamed E

2017년 11월 22일

Not much to learn in this course, basic recommendations can be condensed in one or two lectures

교육 기관: Jordi T A

2017년 8월 28일

A lot of the content seemed redundant both within the lectures and with the previous courses

교육 기관: Clement K

2020년 5월 11일

Interesting but redundant. It's not worth an entire course, even if it's only two weeks

교육 기관: Péter D

2017년 10월 6일

long videos saying actually very little ... disappointment

교육 기관: Andrey L

2017년 10월 29일

Quite boring and not so interactive like the first course

교육 기관: harsh s

2020년 9월 22일

good but more theoretical course rather than pratical

교육 기관: Kaarthik S

2020년 5월 25일

this is the boring course in the specialization

교육 기관: Thomas A

2019년 10월 2일

Can be better, but there's way too much fluff

교육 기관: Till R

2019년 3월 2일

Some things are best learned from experience.

교육 기관: Subhadeep R

2018년 9월 25일

Frankly I didn't find this to be very useful.

교육 기관: Hernan F D

2019년 12월 17일

There is no a lot of content in this course

교육 기관: Aloys N

2019년 9월 20일

Missing a bit of practical Python exercises

교육 기관: Ofer G

2019년 7월 9일

Pretty basic and not enough practical

교육 기관: 2k19ec173 s

2021년 4월 4일

please work on the audio quality

교육 기관: Agniteja M

2019년 10월 2일

Useful only for beginners

교육 기관: Chaobin Y

2017년 10월 12일

Too little materials.

교육 기관: Vinayagamurthy.M

2020년 1월 5일

Very theoritic

교육 기관: Gerrit V

2019년 8월 19일

Much too slow

교육 기관: Zeyi W

2018년 4월 8일

Too short

교육 기관: Christof H

2017년 9월 18일

no praxis

교육 기관: 태윤 김

2018년 7월 9일

no funny

교육 기관: NATHAN W

2021년 5월 3일

extremely overgeneralized with no information on how to apply any of these concepts to an industry application. No manufacturing facility birdwatches as a source of income.