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Отзывы учащихся о курсе Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization от партнера

Оценки: 60,117
Рецензии: 6,959

О курсе

In the second course of the Deep Learning Specialization, you will open the deep learning black box to understand the processes that drive performance and generate good results systematically. By the end, you will learn the best practices to train and develop test sets and analyze bias/variance for building deep learning applications; be able to use standard neural network techniques such as initialization, L2 and dropout regularization, hyperparameter tuning, batch normalization, and gradient checking; implement and apply a variety of optimization algorithms, such as mini-batch gradient descent, Momentum, RMSprop and Adam, and check for their convergence; and implement a neural network in TensorFlow. 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

13 янв. 2020 г.

After completion of this course I know which values to look at if my ML model is not performing up to the task. It is a detailed but not too complicated course to understand the parameters used by ML.

8 окт. 2019 г.

I really enjoyed this course. Many details are given here that are crucial to gain experience and tips on things that looks easy at first sight but are important for a faster ML project implementation

Фильтр по:

6851–6875 из 6,905 отзывов о курсе Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

автор: Jérôme C

14 окт. 2018 г.

Need more training on Tensorflow, imho

автор: Juan J D

11 сент. 2017 г.

tensorflow subject was to superficial

автор: Weeha G

25 июля 2021 г.

Assignment of week 3 is toooo brief.

автор: SATHVIK S

26 июля 2020 г.

Can dive deeper into the mathematics

автор: Trevor M

23 нояб. 2020 г.

good lectures terrible exercises

автор: Maisam S W

4 окт. 2017 г.

I still find tensorflow hard.

автор: Andrey L

1 окт. 2017 г.

week 2 was extremely boring

автор: Cheran V

9 мая 2020 г.

Outdated with Tensorflow 1


11 мар. 2018 г.

Again, nice videos but not

автор: Matthew P

3 сент. 2021 г.

Focused a bit on minutia.

автор: Adam G

11 июля 2020 г.

Multiple grading issues.

автор: Chaitanya M

1 июля 2020 г.

could be more engaging

автор: Patrick C N

8 янв. 2020 г.

Update for TF2.0 :)

автор: Алексей А

7 сент. 2017 г.

Looks raw yet.

автор: Ilkhom

21 мар. 2019 г.

awful sound

автор: Akhilesh

14 мар. 2018 г.

enjoyed :)

автор: zhesihuang

3 мар. 2019 г.


автор: CARLOS G G

14 июля 2018 г.


автор: Long H N

12 февр. 2019 г.


автор: KimSangsoo

17 сент. 2018 г.


автор: Sameer C

21 окт. 2021 г.

Terrible construction of programming exercises. They either end up being extremely trivial or vert obfuscated. Sometimes too much information is given with no incentive to think or too little information is given leading to a deadlock. Week 3 of this course is utterly trash. Course content feels rushed and the programming exercise does not explain anything or clear any doubts. Why on earth do I have to do so little in these programming exercises. Why can't you make us write the little helper functions and plotters and the compiled model.

автор: Sébastien C

4 авг. 2020 г.

Course covers the most important parts of hyperparameter tuning, regularization and optimization.

As a general remark for this specialization, the exercices do not provide any value. We just have to fill in some lines and submit our work.

As I tend to "learn by doing" I had to look for other tutorials and projects on other platforms (Kaggle, MachineLearningMastery's website) in order to complete my learning.

автор: Fabrizio N

7 дек. 2018 г.

Good course content and clear exposition by Andrew. The course material however is not of a good standard. The slides can be downloaded but after all the hand scribbles by the tutor, they are barely decifrable. Some are just blank pages that need to be filled in with screenshots from of the videos. The assignements are often just a copy and paste exercise, and Jupyter crashes cause frequent loss of work.

автор: Goda D R

14 февр. 2020 г.

The video content is very good to get a good hang of theoretical aspects but the programming assignments are too spoon-fed because of which after doing filling the blanks, you don't feel confident enough to implement the same on your own. Instead the assignments should be changed to cases where instructions are given in words and entire function should be implemented by students.

автор: André Ø

30 нояб. 2017 г.

The TensorFlow part of the course felt out of place and not of the same quality as the previous material. It would have been better if another week was spent using TensorFlow to actually improving a NN and not just copy-paste an example into the assignment. Even after using TensorFlow in the assigment and passing, working with TensorFlow still