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Structuring Machine Learning Projects(으)로 돌아가기

deeplearning.ai의 Structuring Machine Learning Projects 학습자 리뷰 및 피드백

4.8
별점
40,709개의 평가
4,502개의 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.

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!).

필터링 기준:

Structuring Machine Learning Projects의 4,457개 리뷰 중 4251~4275

교육 기관: Mayur S

May 26, 2020

The course material can be clubbed with existing courses. It would have been much more meaningful with some examples and hands-on assignments

교육 기관: Rindra R

Oct 11, 2017

Covered important topics and real-world project considerations. However, the content and assignments are too short to make it a full course.

교육 기관: Daniel K

Jun 25, 2020

This time it was not that well-structured than the previous courses. I thought we would learn how to structure step by step an ML project.

교육 기관: José G

Apr 19, 2020

Lots of information, few knowledge

Change name to "Struc. Deep Learning Projects", all other forms of ML not considered, specially for P2.

교육 기관: Eric K

Jul 21, 2018

Too much similar material to the prior course, and only two simple quizzes, no hands-on programming assignments like in earlier courses.

교육 기관: Eric M

Oct 20, 2017

A fundamentally very good course with a few technical gltiches that can be easily corrected and some confusing elements to be clarified.

교육 기관: Bongsang K

May 21, 2018

I think this lecture is important for every research scientist. However, there was no programming examples so I was confused sometimes.

교육 기관: Michael L

May 02, 2018

No programming assignments or labs, so too much theory, and too little chance to put same into practice. Not a good value for my money.

교육 기관: Max S

Dec 13, 2017

Still good but getting much sloppier. Bad editing of the videos, some exercises plain wrong and staff not reacting to forum posts, etc.

교육 기관: Lars L

Dec 30, 2017

Course materials need some cleanup. Were a number of audio blips, in the video. Material was good but just didn't seem as polished.

교육 기관: nitin s

Jun 25, 2020

Decent learning. Though quite some stuff, I felt as repetitive and obvious.

I wish there was some programming exposure as well here

교육 기관: Taavi K

Nov 30, 2017

Too short on its own (took half a day to go through the whole thing), could have been combined with Course 2 of the specialization.

교육 기관: sai r t

Aug 06, 2018

this session was good it would be more better if they provided the code of them..so that we could be abke to learn more from them

교육 기관: Dennis G

Nov 24, 2017

Felt a bit rushed, each video was full of good tips but personally I think each video should have been a jupyternotebook instead.

교육 기관: Massimo A

Nov 18, 2017

More theoretical than the other courses in the specialisation but still very high quality.

Short but with a lot of information.

교육 기관: David P

Oct 17, 2017

Not nearly as good as the first two courses. These two weeks should probably be added into the second course at some point...

교육 기관: Oliver O

Oct 16, 2017

Would like more applied discussion and for it to be Longer. In particular I would like to see a discussion on class imbalance.

교육 기관: Shuai W

Sep 19, 2017

The content of this course is a bit too little for me.

However, it provides useful guidance for my projects. Much appreciated!

교육 기관: Gary S

Sep 16, 2017

Not nearly as valuable as the first Deep Learning course. And the questions posed in the quizzes seemed far more subjective.

교육 기관: Pejman M

Oct 21, 2017

Programming practices with TensorFlow should have continued in this course. Unfortunately, these two weeks were all talking.

교육 기관: Mustafa H

Jul 17, 2018

This course does discuss interesting and important subjects but I feel it can be combined with course 2 of this series

교육 기관: Ahmed A

Jul 10, 2018

course is very good have a lot of important theory, it will be amazing if become 3 weeks with programming assignments.

교육 기관: Kevin Q

Mar 19, 2018

lot of issues with assignments and ambiguous quiz questions this time around, not as polished as other Andrew courses

교육 기관: Arghya R

Sep 19, 2017

Could have more case studies and above all. Also programing assignments on self driving car could have been better