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Название: Applied Deep Learning: A Case-Based Approach to Understanding Deep Neural Networks
Год: 2018
Издатель: Apress
Кол-во страниц: 402
Язык: english
Формат: PDF
Описание:
Work with advanced topics in deep learning, such as optimization algorithms, hyper-parameter tuning, dropout, and error analysis as well as strategies to address typical problems encountered when training deep neural networks. You'll begin by studying the activation functions mostly with a single neuron (ReLu, sigmoid, and Swish), seeing how to perform linear and logistic regression using TensorFlow, and choosing the right cost function.
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Название: Applied Deep Learning: A Case-Based Approach to Understanding Deep Neural Networks
Год: 2018
Издатель: Apress
Кол-во страниц: 402
Язык: english
Формат: PDF
Описание:
Work with advanced topics in deep learning, such as optimization algorithms, hyper-parameter tuning, dropout, and error analysis as well as strategies to address typical problems encountered when training deep neural networks. You'll begin by studying the activation functions mostly with a single neuron (ReLu, sigmoid, and Swish), seeing how to perform linear and logistic regression using TensorFlow, and choosing the right cost function.
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