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Отзывы учащихся о курсе Structuring Machine Learning Projects от партнера deeplearning.ai

4.8
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Оценки: 40,709
Рецензии: 4,502

О курсе

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....

Лучшие рецензии

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!).

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3676–3700 из 4,456 отзывов о курсе Structuring Machine Learning Projects

автор: Carlos S C V

Apr 16, 2020

Me gustó el curso, pero creo que algunas lecciones fueron un poco más largas de lo necesario. Debo agregar que me gustaron mucho los simuladores, creo que me ayudaron mucho

автор: Vinod S

Nov 19, 2017

Helps clearly in understanding practical aspects of deep learning. An additional week, highlighting the aspects of productionizing a deep learning project would have helped

автор: Palathingal F

Sep 28, 2017

A unique course to understand the process of establishing a ML project. But lacks tools information and a more structured definition of the process. A bit too theoretical.

автор: Mahnaz A K

Jul 02, 2019

Thanks for the practical tips and insights from real projects.

Your pool of heroes of deep learning is very skewed. If the field is so skewed, then it's a bigger problem.

автор: Vivek V A

Feb 13, 2019

Good course for the ones who already started developing ML systems. This will help us in improving the ML systems and identify what can be done for which kind of problems

автор: Ivan L

Jun 25, 2019

Most of the material was quite useful, but some was, perhaps, too obvious. Also, some things were discussed too thoroughly, and, in my opinion, that was a waste of time.

автор: Aliaksei A

Sep 14, 2017

Would be great to obtain more concrete information.

For example, instead of "requires much more training data" to obtain "requires ~1'000'000 samples instead of ~100'000"

автор: Rafal S

Jul 22, 2019

Excellent content overall. However, reiterates some of the knowledge already presented in the two previous courses of the specialization. Lacks programming assignments.

автор: Amir R K P

Dec 07, 2018

I wish there was more examples, visualization and depiction of work with referral to papers or experiment here. or perhaps a bit of project management, data management.

автор: Pete C

Jun 24, 2018

Enjoyable, but felt a little less challenging and more hastily assembled. Regardless, the material is valuable and as always, a pleasure to be instructed by Andrew Ng.

автор: Lars R

Aug 29, 2017

The course material is relevant and useful, however, I agree with other reviewers that these 2 weeks should rather be a 1-2 weeks addition to one of the other courses.

автор: Andrew R

Apr 30, 2018

Quick course. Worth taking because gives some practical guidance on what avenues to pursue when finding a optimal model (which takes into account human time required)

автор: Poorya F

Dec 11, 2017

The first week is too long with repetitive materials. The second week is very interesting. However, I wish the course was designed such that it required some coding.

автор: Hany T

Aug 27, 2019

Great course, great professor .. the only issue is that I feel sleepy every time I watch the videos :), it's some how single tone. Also the audio could be improved.

автор: Karthikeyan C (

Mar 16, 2020

It is always important to learn above the problem-solving methods and tools. This course teaches the complete diagnosis methodologies for Machine Learning problems

автор: Mehran M

Jun 25, 2018

Overall, very informative, however I think the content of this course could be divided between the first and the second course.More assignments would've been nice.

автор: Rajesh S

Nov 26, 2017

Lots of practical advice and ideas on how to work on actual projects and things to look out for. Great stuff. Wish it had a few programming exercises or a project.

автор: Ross K

Aug 30, 2017

Useful introduction to meta-level principles of machine learning process management, but not quite as groundbreaking or well-instructed as the previous two courses

автор: karthik T S

Apr 13, 2020

A real time project or programming assignment could improve our confidence level.

All of these courses if it had readable material along with video, it'd be great.

автор: 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!

автор: 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.

автор: 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.

автор: 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.

автор: 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

автор: 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.