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Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization,

Оценки: 31,803
Рецензии: 3,440

Об этом курсе

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....

Лучшие рецензии

автор: 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.

автор: 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.

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Рецензии: 3,375

автор: Matthew Glass

Apr 18, 2019

Very good course. Andrew really steps it up in part two with lots of valuable information.

автор: Rafael Araujo

Apr 17, 2019

Excelente curso, recomendo fortemente, principalmente pela base matemática fornecida.

автор: Jenil Mehta

Apr 17, 2019

nice course

автор: 紫色人的心

Apr 15, 2019


автор: Md. Redwan Karim Sony

Apr 15, 2019

Excellent course. When I learned about implementing ANN using keras in python, I just followed some tutorials but didn't understand the tradeoff among many parameters like the number of layers, nodes per layers, epochs, batch size, etc. This course is helping me a lot to understand them. Great work Mr. Andrew Ng. :)

автор: Tang Yuanyuan

Apr 15, 2019

very practical.

автор: 董云鹏

Apr 14, 2019

very useful

автор: Mohamadreza

Apr 14, 2019

That was AWSOME! It was really good and I'm pretty sure it would help me through my study and career!


автор: 郑笙桦

Apr 14, 2019

Means a lot.

автор: Arun Siddharth

Apr 13, 2019

This course helped me to understand the practical aspect of NN. Tuning of Hyper parameters, Regularization , Algos like ADAM are important for fast and accurate training. I hope i could make use of information in future. However this course gives very little introduction to tensorflow and somewhat doesn't satisfies students i believe. Prof. Andrew Ng gives a fantastic lectures covering all important aspects in details with patience.