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Structuring Machine Learning Projects(으)로 돌아가기

deeplearning.ai의 Structuring Machine Learning Projects 학습자 리뷰 및 피드백

4.8
35,373개의 평가
3,714개의 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

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.

DC

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!

필터링 기준:

Structuring Machine Learning Projects의 3,671개 리뷰 중 3026~3050

교육 기관: SYZ

Dec 10, 2018

Hope to have coding practices for the second week's materials.

Anyway, the current course is already very helpful. Thanks to Andrew and all staff behind the scene!

교육 기관: Jussi V

Feb 18, 2018

Content is good, but a bit thin... This course makes sense as part of the deep learning specialisation, even if this is a bit too short to be a course of its own.

교육 기관: Boris D

Jul 23, 2019

A bit less interesting than the others I think. To me the whole first week was full of obvious stuff. The second week, however, was very interesting and helpful.

교육 기관: Subash P

Oct 23, 2017

There was lot of theory and probably not one of my strengths. However the content is very useful for bringing some structure to machine learning problem solving.

교육 기관: Jaime R

Nov 20, 2018

This course could have just been an extra week or two of course 2. It doesn't have the depth of the others, although it is very practical and I like the content

교육 기관: Calvin K

Mar 04, 2018

Good advice on how to work on a machine learning project from the ground up. Tho most of the material is already covered in Ng's Machine Learning Yearning book.

교육 기관: Deleted A

Nov 19, 2017

Nice to see a course on machine learning about the 'other stuff' around machine learning. However, links didn't work half the time and it was a bit unpolished.

교육 기관: Klas K

Oct 13, 2017

Some of the lectures feel quite lengthy and repeat stuff. It seems to be easily possible to condense into one week which could be added to the previous course.

교육 기관: Anahita P

Jan 19, 2019

a lot of topics are covered in machine learning course, but this has an upgrade to input from previous course due to changes has happened in AI in last years.

교육 기관: David M M

Nov 17, 2018

Valuable tips to apply in machine learning projects. I'd like to have some programming assignment that gives opportunity to practice some of those techniques.

교육 기관: Luis A H L

Apr 20, 2018

Es muy bueno el curso lo recomiendo si se desea tener un conocimiento general sobre los aspectos a considerar en las etapas del desarrollo de proyectos de ML.

교육 기관: Giacomo

Mar 19, 2018

Advanced course, as always well done :D

Anyway, something for me strange is that there are only quitz but not exercices in Python/Tensor Flow... This is a pity

교육 기관: Alejandro Z

Sep 22, 2017

I loved the lessons, they are very practical. The only thing that I think could be improved are some of the quizz questions are worded in a bit ambiguous way.

교육 기관: Dinh T T

Feb 07, 2019

It's an useful course to give me how to analyze error and give me some advice how to apply transfer learning and multitask learning. Thank for your course.

교육 기관: Diwakar R

May 11, 2018

I felt that this course was too slow for my liking. While I agree this helps a lot, But I watched all the videos at 1.25x the speed so that I dont get bored

교육 기관: Gagan G

May 06, 2019

It doesn't have coding but it teaches thing that will really help in real projects when we will need to decide best approach based on multiple data points.

교육 기관: 钟胜杰

Nov 19, 2018

The courses of this two weeks make me confused because i have't built a machine learning systems fully by myself yet , so i found those classes boring.0.0

교육 기관: Robert N C

Aug 02, 2018

Not as helpful or practical as earlier lessons, but nonetheless important high-level advice. Perhaps there was a better way to test knowledge than a quiz?

교육 기관: Simon S

Oct 23, 2018

Still a great course, but compared to the pervious two, this seems to be a bit less useful and practical and there are a few mistakes with cutting, etc.

교육 기관: BINGNI G

Sep 12, 2018

It may be useful in the future, but since I don't have any large project experience in the real world, I feel a little boring while taking this course.

교육 기관: Osbert Z

Feb 16, 2018

Some content was a bit superficial. Many concepts regarding approach to machine learning projects were useful. Found the "flight simulators" were not s

교육 기관: John F

Jan 28, 2018

Quite a lot useful information for structuring deep learning projects, but also quite some errors in the course contents. Hope them will be fixed soon.

교육 기관: John E

Oct 04, 2017

Overall a nice approach to understand how to tune the learning algorithms. There are some production/editing issues in the videos that are distracting.

교육 기관: eddy k

Oct 30, 2017

excellent practical and insightful strategies from years of andrew's experience, i wish there were more hands on labs to practice some of the concepts

교육 기관: Robert P

Apr 17, 2018

The content is well worth going through. While the "flight simulator" approach was certainly beneficial, I wish there had been programming exercises.