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Отзывы учащихся о курсе Structuring Machine Learning Projects от партнера

Оценки: 48,223
Рецензии: 5,531

О курсе

In the third course of the Deep Learning Specialization, you will learn how to build a successful machine learning project and get to practice decision-making as a machine learning project leader. By the end, you will be able to diagnose errors in a machine learning system; prioritize strategies for reducing errors; understand complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance; and apply end-to-end learning, transfer learning, and multi-task learning. This is also a standalone course for learners who have basic machine learning knowledge. This course draws on Andrew Ng’s experience building and shipping many deep learning products. If you aspire to become a technical leader who can set the direction for an AI team, this course provides the "industry experience" that you might otherwise get only after years of ML work experience. The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI....

Лучшие рецензии


1 дек. 2020 г.

I learned so many things in this module. I learned that how to do error analysis and different kind of the learning techniques. Thanks Professor Andrew Ng to provide such a valuable and updated stuff.


1 июля 2020 г.

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!).

Фильтр по:

5276–5300 из 5,498 отзывов о курсе Structuring Machine Learning Projects

автор: Denys G

23 нояб. 2017 г.

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

автор: Massimo A

18 нояб. 2017 г.

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

Short but with a lot of information.

автор: David P

17 окт. 2017 г.

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

автор: Oliver O

16 окт. 2017 г.

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

автор: Shuai W

19 сент. 2017 г.

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

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

автор: Gary S

15 сент. 2017 г.

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

автор: Pejman M

21 окт. 2017 г.

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

автор: Nithin V

3 янв. 2021 г.

Need more quizzes, assignments to deepen the understanding, But otherwise thank you Andrew Ng for presenting this material

автор: Panos K

18 апр. 2021 г.

The pace of the first part of the course was too slow. The second part (from Transfer learning onwards) was much better.

автор: Mustafa H

16 июля 2018 г.

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

автор: Ahmed A

10 июля 2018 г.

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

автор: Kevin Q

19 мар. 2018 г.

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

автор: Arghya R

19 сент. 2017 г.

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

автор: Okhtay A

5 апр. 2020 г.

A bit too free form compared to the other courses in deep learning specialization, but maybe that was the goal.

автор: Masih B

18 июля 2020 г.

This course could be way more better, if it also focused on codeing with tensorflow (like the previous course)

автор: Janet C

29 июня 2019 г.

Overview of the machine learning process. No projects or sample code to actually organize the ideas into code.

автор: Aniruddh B

16 апр. 2020 г.

Very nice, but I don't believe the content merits a full course. It could be integrated with courses 1 and 2.

автор: Vitaliy

28 февр. 2018 г.

To much talk but understandable. Need something like programming examples with different data distributions.

автор: Rob W

12 мая 2018 г.

Seemed to be information that could have been included in another course rather than its own 2 week course.

автор: Idan P

28 мая 2018 г.

Lectures can be summed up by: "use common sense".

Quiz can be summed up by "to pass, use OUR common sense".

автор: Abd-Elrahman B

21 дек. 2017 г.

The quiz questions are quite confusing and some of them are not consistent with the content of the videos.

автор: Rishabh B

3 янв. 2020 г.

Slightly repetitive from previous courses. Could have been integrated with the future or previous course.

автор: Barnoviciu E

18 янв. 2021 г.

Filled like it could be condensed in a lot less, probably a filler to fill the 5 courses "requirement??"

автор: Tim U

11 янв. 2020 г.

More quizzes or scenario-based examples or exercises at the end in coding. This felt thin in content.

автор: Iam P d S

14 мар. 2018 г.

This course was shorter and didn't have any programming assignments. Could've been part of course 2.