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Отзывы учащихся о курсе Structuring Machine Learning Projects от партнера

Оценки: 45,286
Рецензии: 5,159

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

30 мар. 2020 г.

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.

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:

4601–4625 из 5,101 отзывов о курсе Structuring Machine Learning Projects

автор: WEIJIAN K

15 нояб. 2017 г.

You can know well a lot of strategy in machine learning

автор: B S K

14 июля 2020 г.

Good teaching of practical approaches and nice quizzes

автор: 王毅

24 дек. 2019 г.

the content is good, but the videos are not well made.

автор: Shuochen Z

17 февр. 2019 г.


автор: Gundreddy L M

11 сент. 2018 г.

excerice should be given for this one proper user case

автор: Alexey S

22 окт. 2017 г.

Good class, but 2 previous are much better and useful.

автор: Lei C

25 сент. 2017 г.

the answer of the assignment is a little bit arguable.

автор: SANJAY P

6 окт. 2020 г.

Content is good. Presentation could have been better.

автор: Kumari P

28 мая 2020 г.

machine learning project are highly iterative as you.

автор: diego s

18 февр. 2020 г.

I miss notebooks for practice, besides questionnaires

автор: Xinghua J

6 сент. 2019 г.

If there is some coding practice, it would be better

автор: Pranjal V

11 июля 2020 г.

Very well explained but needs more reading material.

автор: Hee s K

18 апр. 2018 г.

It is an unique lecture providing empirical advises.

автор: Pablo L

30 окт. 2017 г.

Great set of guidelines. Mostly theoretical, though.

автор: Cristina G F

22 окт. 2017 г.

Concrete reminders of important and practical points

автор: Ktawut T

10 окт. 2017 г.

Very useful materials for leading a ML research team

автор: awalin s

29 сент. 2017 г.

interesting insights about real world implementation

автор: Yu L

3 апр. 2020 г.

would like to have more excercise related to coding

автор: Mage K

7 мар. 2018 г.

Would've liked to have some programming assignments

автор: Carlisle

20 авг. 2017 г.

Introduced a lot on engineering project experiences

автор: Marcelo A H

29 мая 2020 г.

Very interesting topics were shown in this course.

автор: William L

17 апр. 2020 г.

Very useful knowledge that is not commonly taught.

автор: Alvaro G d P

27 нояб. 2017 г.

Interesting but perhaps we could have gone deeper.

автор: John H

26 авг. 2017 г.

Is the flight simulator hw going to be added soon?

автор: Pat B

8 дек. 2019 г.

Great course. I liked the compact, 2-week format.