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Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization(으)로 돌아가기

Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization, deeplearning.ai

4.9
33,202개의 평가
3,559개의 리뷰

About this Course

This course will teach you the "magic" of getting deep learning to work well. Rather than the deep learning process being a black box, you will understand what drives performance, and be able to more systematically get good results. You will also learn TensorFlow. After 3 weeks, you will: - Understand industry best-practices for building deep learning applications. - Be able to effectively use the common neural network "tricks", including initialization, L2 and dropout regularization, Batch normalization, gradient checking, - Be able to implement and apply a variety of optimization algorithms, such as mini-batch gradient descent, Momentum, RMSprop and Adam, and check for their convergence. - Understand new best-practices for the deep learning era of how to set up train/dev/test sets and analyze bias/variance - Be able to implement a neural network in TensorFlow. This is the second course of the Deep Learning Specialization....

최상위 리뷰

대학: XG

Oct 31, 2017

Thank you Andrew!! I know start to use Tensorflow, however, this tool is not well for a research goal. Maybe, pytorch could be considered in the future!! And let us know how to use pytorch in Windows.

대학: CV

Dec 24, 2017

Exceptional Course, the Hyper parameters explanations are excellent every tip and advice provided help me so much to build better models, I also really liked the introduction of Tensor Flow\n\nThanks.

필터링 기준:

3,505개의 리뷰

대학: Yongjian Feng

May 25, 2019

Very interesting.

대학: ANSHUMAN SRIVASTAVA

May 25, 2019

This was a very interesting and different course from others. I found it very helpful

for improving the NNs and the techniques taught with assignments give a well insight so as to how the problem should be dealt with.

Thank you to teachers and to Coursera.

대학: Philippe Kalitine

May 25, 2019

Yet difficult theoretical part, but a very helpful course that helps to understand what is going on in the DeepLearning black box. I definitely recommend it!

대학: Manish Kumar

May 25, 2019

very good content

대학: Binjer

May 25, 2019

讲解的非常细致和深入,对初学者友好。而随着对ML领域的理解不断丰富,也会产生更深入的理解。非常感谢为这门课程做出贡献的所有人

대학: George Olawunmi Olaboopo

May 25, 2019

Great!

대학: Chaminda Wijayasundara

May 24, 2019

great learning

대학: Zimo Zhao

May 24, 2019

The final project has problems associating with itself...

대학: Vignesh Sivakumar

May 24, 2019

I got to know the optimization algorithms to use and also the Tensorflow programming framework in depth. It was a really useful course.

대학: guofei

May 24, 2019

Very Helpful !