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48,889 Bewertungen

Über den Kurs

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....



1. Juli 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!).


30. März 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.

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5001 - 5025 von 5,576 Bewertungen für Structuring Machine Learning Projects

von Yue Z

23. Feb. 2020

complementary material for the book "machine learning yarning"


12. März 2018

Lot of theory was their. Good but felt asleep after some time.

von Wenhai Z

27. Nov. 2017

I would wish there were more programming practice assignments.

von Kyle H

22. Okt. 2017

Contained all good content, there just wasn't very much of it.

von Daniel L

21. Sep. 2020

The course is so useful, but sometimes the voice turns so low

von Paweł P

11. Okt. 2019

Good overview of the problems occuring while training models.

von Sathiraju E

25. Mai 2019

Thank you, Andrew.

This course was very helpful though theory.

von Daniel Z

14. Aug. 2018

Good course. It would be better with programming assignments.

von Antonio H

2. Juli 2018

I could not do the flight simulator test, it was not working.

von Youjiang Y

16. Jan. 2018

It will be really nice if there is assignment for this course

von Jeremy O

19. Apr. 2021

Was hoping to get some insight into architectural decisions.

von Dioselin E B P

13. Jan. 2021

It's much information for only a one questionnaire for week!

von zhang l

16. März 2020

Some of the questions in the quiz set seems a bit confusing.

von gayatri h

4. Juni 2019

It gives the idea about real life machine learning problems.

von David d V

24. Mai 2018

It would have been great to add some programming assignments

von Jeff O

11. Sep. 2017

Good material, just wish it had more "labs" to work through.

von Juan C M S

8. Juni 2020

In some occasions it's been has a bit redundant information

von Pranav B

30. Jan. 2020

Good Course for Beginners need more programming assignments

von Gil E B

29. Juli 2019

Good Course to learn production pipelines for practical use

von Fereydoon V

2. Feb. 2018

Hope we had programming assignment for this course as well!

von Nandigama V

3. Jan. 2018

Very good course, It should be last course in specilization

von Richard M

14. Okt. 2020

Interesting ideas, but not as good structured as course 1.

von Pakin P

28. Nov. 2019

Thanks I learn a lot of real world application and problem

von Peter K

23. März 2019

강의 후반부 (2주차) 에 강의 속도가 인위적으로 조정된거 같습니다. 속도가 빨라 이질감이 느껴졌습니다.

von Akshat A

23. Feb. 2019

Curated content, quite exclusive indeed. Respect to Dr. Ng