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Bewertung und Feedback des Lernenden für Structuring Machine Learning Projects von

48,216 Bewertungen
5,530 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....



22. Nov. 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.


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!).

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5451 - 5475 von 5,497 Bewertungen für Structuring Machine Learning Projects

von Vishal K

17. Dez. 2017

The weakest of the three so far - comparatively lots of fluff. Unclear definitions with lots of perhapses and maybes.

von Benoit D

15. Aug. 2017

I have been working in industry for 5 years now and this are not really the problems we encounter in practice.

von Mads E H

26. Okt. 2017

Not applicable enough. I think you need more tooling around DL before these meta lectures makes sense.

von Dafydd S

23. Okt. 2017

Had the feeling of a "filler" course although it was interesting to hear about the various challenges

von Alexander V

25. Feb. 2018

A lot of very common-place suggestions that could just as easily be conveyed in a third of the time.

von Nahuel S R

4. März 2020

Demasiado contenido teórico sin aplicaciones prácticas reales que permitan consolidar lo aprendido

von Peter E

2. Mai 2018

Too theoretical. It would be good to have some practical (programming) assignments here as well.

von Mohamed E

22. Nov. 2017

Not much to learn in this course, basic recommendations can be condensed in one or two lectures

von Jordi T A

28. Aug. 2017

A lot of the content seemed redundant both within the lectures and with the previous courses

von Clement K

11. Mai 2020

Interesting but redundant. It's not worth an entire course, even if it's only two weeks

von Péter D

6. Okt. 2017

long videos saying actually very little ... disappointment

von Andrey L

29. Okt. 2017

Quite boring and not so interactive like the first course

von harsh s

22. Sep. 2020

good but more theoretical course rather than pratical

von Kaarthik S

25. Mai 2020

this is the boring course in the specialization

von Thomas A

2. Okt. 2019

Can be better, but there's way too much fluff

von Till R

2. März 2019

Some things are best learned from experience.

von Subhadeep R

25. Sep. 2018

Frankly I didn't find this to be very useful.

von Hernan F D

17. Dez. 2019

There is no a lot of content in this course

von Aloys N

20. Sep. 2019

Missing a bit of practical Python exercises

von Ofer G

9. Juli 2019

Pretty basic and not enough practical

von 2k19ec173 s

4. Apr. 2021

please work on the audio quality

von Agniteja M

2. Okt. 2019

Useful only for beginners

von Chaobin Y

12. Okt. 2017

Too little materials.

von Vinayagamurthy.M

5. Jan. 2020

Very theoritic

von Gerrit V

19. Aug. 2019

Much too slow