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

4.8
звезд
Оценки: 43,402
Рецензии: 4,886

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

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!).

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.

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4576–4600 из 4,834 отзывов о курсе Structuring Machine Learning Projects

автор: Gabriel S M

Oct 22, 2017

It is a good course because it highlights practical aspects of implementing ML. Some of the test questions were a bit ambiguous though.

I'd also like to have seen Transfer/Multi-task learning implementation exercises.

автор: Noga A

Jul 21, 2020

I understand why this course is important, but for me it was the least favorite course so far. Some of the videos were too long and repeat themselves. Maybe it's because I have knowledge in machine learning already.

автор: Tinsae G A

Feb 12, 2018

This course is full of intuitions that are very difficult to remember at once. The quiz is very hard and mind teasing. For better confidence, I would like if you add one more case study.

In general the course is good

автор: Bjorn E

Sep 09, 2019

Interesting and practical information, but it felt stretched out in an attempt to create a two-week course. With some editing and less repeated information this could be one week that would fit in the prior course.

автор: RB

Jan 31, 2018

Good course to learn about structuring the projects and carrying out error analysis. I wish there were some assignment to work on in addition to the case study quizzes. Assignment really help us learn effectively

автор: Francisco S R

Oct 25, 2017

The course was just a bunch of tips and suggestions. Yes, they are useful, but given the empirical nature of machine learning I would expect those tips to be accompanied by practical applications and homework.

автор: Amit P

Aug 21, 2017

I expected more. The videos were a little long and repetitive. The content was important, though. Maybe the course materials could be squeezed into one week and combined with the previous deep learning course.

автор: Viswajith K N

Jun 24, 2018

THe course was challenging and had valuable inputs. But it would be even more wonderful if we got to work on some portion of the case studies as a capstone project at the very least. Else Its a 5 star course.

автор: daniele r

Jul 15, 2019

Good for the numerous hints about practical issues such as different distributions on train/dev/set. Very bad for the lack of hands-on assignments. Good practical advices but no occasion to see them working!

автор: John O

Dec 16, 2017

The quality of the course is not up to par with the other courses in the specialization. There is very little content and it is gone through too slowly. There are also more bugs and errors in the exercises.

автор: 臧雷

Sep 05, 2017

Most of the materials in this course is tedious and have already been taught in previous courses. But I suggest the Transfer Learning and Multi-task Learning part, as well as the end-to-end learning part.

автор: Wells J

Dec 16, 2017

The course was misleading on what homework there was (machine learning flight simulation?) There was no homework. and the lectures were pretty bland compared to other courses in this specialty.

автор: Karthik R

Mar 04, 2018

Transfer Learning and Multi-Task learning discussed in the course would greatly benefit from having programming assignments where people can play around with the data and learn confidently.

автор: Andrew W

Aug 05, 2019

Good information about how to structure projects and how to boost performance. Not very hands-on however. Fits in well with the Specialization though as a break before CNN's and sequences.

автор: Daniel C

Nov 19, 2017

Not as helpful... just a few suggestions and ideas... but there's no great application of the information learned here like a walk-through project or something with code, that's graded.

автор: Luiz C

Oct 22, 2017

less useful than previous courses.

Would appreciate to go much deeper in directions like CNN, RNN, RL and review Unsupervised Learning (which was too light, ... no mention about RBM)

автор: Akshay S

Jun 18, 2020

It was very theoretical and subjective.

It would be useful if the learner has some more experience in DNN than currently expected.

But I definitely enjoyed 2nd week of the course.

автор: Andrew C

Oct 29, 2017

Interesting content, but lacking in real work. As with all of the deeplearning.ai courses thus far, the multiple choice questions are frequently ambiguous and poorly worded.

автор: Zsolt K

Sep 24, 2018

The information is really basic, most of it is self explanatory. This shouldn't be a course on its own, rather maybe a week/half weeks worth of material in another course.

автор: Sherif A

Nov 25, 2017

This course is too subjective. Andrew shares his experience in a structured way in the lecture. However, I feel that correct structuring decisions need to be brainstormed.

автор: Patrick F

Dec 12, 2019

Seeing different practical use scenarios and adaptions is fine but it got pretty boring without a real application to tune. The Quizzes on the other hand were very good!

автор: Alberto S

May 29, 2018

Although everything taught is relevant, it was too much theoretical. And some of the evaluation questions are not clear (well, at least for non native English speakers).

автор: Daniel V

Feb 26, 2020

Generally useful skills, but the contents partially overlap with previous courses and the overall quality doesn't match the previous courses (eg poor video mastering).

автор: Davide C

Nov 26, 2017

The course was interesting, but in my opinion too theoretical. I preferred the first 2 courses with Python programming. I am now looking forward to the next 2 courses.

автор: Felipe L d S

Jun 08, 2018

Even though some of the content is useful, I feel like this course should be merged with the second one. There is not new information enough to justify a new course.