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Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization に戻る

deeplearning.ai による Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization の受講者のレビューおよびフィードバック

4.9
60,152件の評価
6,964件のレビュー

コースについて

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....

人気のレビュー

NA
2020年1月13日

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.

JS
2021年4月4日

Fantastic course and although it guides you through the course (and may feel less challenging to some) it provides all the building blocks for you to latter apply them to your own interesting project.

フィルター:

Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization: 6851 - 6875 / 6,909 レビュー

by Aashita G

2020年6月1日

fast paced not enough emphasis on topics

by Amod J

2018年3月18日

Want to download my own work but cannot.

by Rachana O

2020年8月17日

Can be done in more interesting manner.

by Mark L

2020年7月16日

great superficial intro to the content

by Jérôme C

2018年10月14日

Need more training on Tensorflow, imho

by Juan J D

2017年9月11日

tensorflow subject was to superficial

by Weeha G

2021年7月25日

Assignment of week 3 is toooo brief.

by SATHVIK S

2020年7月26日

Can dive deeper into the mathematics

by Trevor M

2020年11月23日

good lectures terrible exercises

by Maisam S W

2017年10月4日

I still find tensorflow hard.

by Andrey L

2017年10月1日

week 2 was extremely boring

by Cheran V

2020年5月9日

Outdated with Tensorflow 1

by QUINTANA-AMATE, S

2018年3月11日

Again, nice videos but not

by Matthew P

2021年9月3日

Focused a bit on minutia.

by Adam G

2020年7月11日

Multiple grading issues.

by Chaitanya M

2020年7月1日

could be more engaging

by Patrick C N

2020年1月8日

Update for TF2.0 :)

by Алексей А

2017年9月7日

Looks raw yet.

by Ilkhom

2019年3月21日

awful sound

by Akhilesh

2018年3月14日

enjoyed :)

by zhesihuang

2019年3月3日

good

by CARLOS G G

2018年7月14日

good

by Long H N

2019年2月12日

N/A

by KimSangsoo

2018年9月17日

괜찮음

by Sameer C

2021年10月21日

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.