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48,208 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....



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.


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.

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5326 - 5350 von 5,496 Bewertungen für Structuring Machine Learning Projects


30. Mai 2020

It was awesome but not one of the best courses in the specialization!

von David F

22. Sep. 2017

Good insights, but not much material and no programming assignments.

von Ondrej S

21. Juli 2021

U​sefull but only theorethical course without practical excercises.

von Siddhesh

3. Nov. 2017

It was rather disappointing because it didn't meet my expectations.

von Sébastien C

6. Aug. 2020

Covers interesting concepts at length. Videos could be shortened.

von Lambert R

16. Apr. 2018

Dommage qu'il n'y ait pas de TP dans ce cours (seulement 2 quizz)

von Mike T

24. Juli 2018

I wished there were exercises besides the quizzes in this course

von Anatolii B

1. Okt. 2018

some quiz questions are poorly formed, a little disappointing.

von Emmanuel D M

21. Apr. 2020

I thini the course needs more quizzess and a program exercise

von C. I

17. Aug. 2017

Very short, not many practical examples. Lots of repetitions.

von W S

31. Aug. 2019

Video lectures tend to be repetitious, and can be confusing.

von Anthony M

23. Okt. 2017

Practical knowledge, but I would prefer more hands on coding

von Jiheng R Z

9. Sep. 2017

Quite a few errors and ambiguities in the practice problems.

von Zingg

16. Nov. 2017

The topics are interesting however the content is off par.

von Axel G

14. Juni 2020

Good content, but very focused on Computer Vision and NLP

von Daniel D

4. Sep. 2017

The course es good, but it seems still under development.

von Juan A C A

30. Aug. 2017

It would be better if you include programming exercises.

von A M

13. Jan. 2018

It was hard to keep interested - lost focus many times

von Brandon C

6. Dez. 2018

lacking in the usual engaging programming assignments

von Varun S

23. Sep. 2018

Was expecting more scenarios for real data experience

von Jian Z

6. Nov. 2017


von Bogdan P

19. Sep. 2018

The course is OK, but it lacks programming exercises


20. Juli 2019

Learned new things but the course was boring.......

von Tzushuan W

1. Juni 2019

Wordy and too abstract without hands on experience.

von Evgeny S

5. Apr. 2018

I would rather expect a course more like a capstone