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学生对 提供的 Structuring Machine Learning Projects 的评价和反馈

38,546 个评分
4,216 条评论


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....



Mar 31, 2020

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.


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.


3351 - Structuring Machine Learning Projects 的 3375 个评论(共 4,181 个)

创建者 Samchuk D

Sep 24, 2017

The content of this course is quite unique. Thus it makes it much more interesting and important.

Thank's a lot for this tips!

However it would be nicer if there is some videos practical assignments about tech aspects of implementations of "transfer learning" and "multitask learning"

创建者 Eslam S H

Aug 20, 2018

I got the same feedback for many of my colleagues that this course is not that important and I should start with course #4 instead, but I am glad I didn't there is a lot of insights and experiences in this course that I think it would take anyone many years to conclude by himself.

创建者 Antonio C

Apr 14, 2020

That's a great course to learn some practicalities of deep learning/transfer learning and multitask learning, and when to use different strategies for structuring a project. In my opinion, the course could do with a hands-on programming exercise to help consolidate the learnings.

创建者 Milan S

Jun 01, 2018

Sometimes its become bored who has not any experienced into working on real life ML project because without facing problem you can not understand problem in better way so i recommend course instructure to make this course with little more practical way so that it easy to digest.

创建者 Hans E

Feb 18, 2018

A bit slow going and repetitive (and some simple video editing to remove double sections would improve things). Nevertheless I'm amazed how much I learned or consolidated is just a few evenings of watching these videos. Thanks again! Looking forward to course 4 in this series.

创建者 Srinivas K R

Oct 03, 2017

Thorough and practical guidelines to structure and analyze issues with machine learning projects. Distilled learning presented from a lot of project experience. It would be hard to gain such knowledge without having gone through a number of projects. Accelerates your learning.

创建者 Rahul D

Apr 20, 2019

Machine learning simulator assignments were great, wish we could have more of them both in this course as well as in the other courses in the specialization. Additionally, I would have loved programming assignments that reinforced these largely workflow-related concepts.

创建者 Lester A S D C

Jun 25, 2019

Useful knowledge regarding the efficient practices in the application of machine learning. Mentors doesn't seem as responsive though, compared to the other courses of the specialization. Quizzes were helpful, but needs more justification for some of the correct answers.

创建者 Harshit S

Nov 12, 2017

The course showed the experiences while dealing with machine learning projects but could have been better if the experience would have been shared through practical exercises rather than objective case study.

It would be better if there were programming exercise as well.

创建者 Jihwan M

Sep 15, 2017

I have a feeling that this third course is not yet fully edited. I see some black screens, and sometimes the clips have Andrew speak faster than usual. Nonetheless, the various tips and appropriate actions to take when doing a machine learning project were very useful.

创建者 Akshaya R

Jan 12, 2020

Good explanation for the initial steps of organizing the ML project and the direction to approach the problem accounted for. The quiz was interesting but as it is the same set of questions for any next attempt, I would not say I have mastered the course completely.

创建者 Jean-Simon B

May 08, 2018

Only 2 weeks, good concepts to know. But videos are not "final release" they are not well edited. Some time Andrew repeat the same sentence 2x but they forgot to cut it.

No programming assignment. Although quiz format is fun and you really learn by doing the quiz.

创建者 Bogdan P

Sep 03, 2017

This was a slightly more theoretical course than the first 3 in the Deep Learning specialization and, even thought I enjoyed it, I think the info would stick better if there would have been a programming assignment too (or some other type fo practical application).

创建者 Kalle H

Nov 20, 2017

Nice and concrete examples of what to think of and focus on when trying to improve your machine learning projects. Not as engaging tasks to complete as in the previous courses in this specialisation, however a good change of scenary if you have been doing these.

创建者 Boris V

Jan 21, 2018

Great material, but it's not quite easy to understand it from scratch, if you didn't have such problems yourself (i.e if you have no experience in deep NN training). I've stored this material and going to revisit it after I gain more experience in training NNs.

创建者 Fredrik K

Oct 06, 2017

Great course, however the quiz of week 2 had some ambigious phrasings and I think at least one example (the one with the data synthesis of foggy images) is contradictive of what was taught in the video lessons. Other than that, really good content and teaching!

创建者 Bharath N S

Apr 20, 2019

A lot of concepts were put forward and taught well. If there was a programming assignment as well to back up the concepts that were taught like multi-task learning, how to deal with data mismatch, dividing the total data into train\train-dev\dev\test data etc.

创建者 Sanskar A

Mar 22, 2020

I feel there is a glitch because even after completing the videos, it is not shown as completed and I had to replay them multiple times. Also there is a glitch in the assignment, because the correct answer in one attempt is shown as incorrect in the next try

创建者 Eemeli L

Nov 19, 2019

Great and easy-to-follow introduction to structuring machine learning projects and focusing on what to tune on neural networks. One star left out because the content has not been polished, but there are minor errors here and there with separate corrections.

创建者 Lingjun L

Jun 08, 2019

The course seems a little less concrete than the others in this specialisation. But nevertheless, still a useful building block in anyone's deep learning repertoire. And note it will probably take less time to complete than the others, so plan accordingly.

创建者 Sakares S

Aug 24, 2017

It would be nice if there are hands on assignment or small projects on fine-tuning with existing weight you can found in the internet or multi-task learning project. Overall, it's a great course with many useful technique to try in the real world projects.

创建者 Alejandro J C O

Feb 17, 2020

The course was really great, but a little part of the content was repeated from previous courses of the specialization. Also there should be more quizzes or exercises to master the large amount of practical advices for managing machine learning projects.

创建者 Paul H

Dec 08, 2017

I liked this course, but not as much as the others. It is however setting the foundation for the remainder of the course material. It carries with it wisdom, which I think will make more sense at a later point when confronted with real life challenges

创建者 Clint S

Mar 14, 2020

This is the course that really confirms Andrew Ng's grasp on the practically application of AI and ML. As long as you pay attention to what is said, you will get a lot from this course. I wish there was an edited collection of notes for this course

创建者 Lars O A

May 29, 2018

Very useful part of the course set. Would like it to be slightly longer with more examples of TensorFlow and Keras. I felt that I put to much effort of trying to understand Keras in course number 5 instead of learning the principles and algorithms.