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主题: Deep Learning with Python

摘要: 《 Python深度学习》第二版全面介绍了使用Python和强大的Keras库进行的深度学习领域。 由Keras的创建者Google AI研究人员FrançoisChollet撰写,此修订版已更新了新章节,新工具和最新研究中的尖端技术。 读者将通过实际示例和直观的说明来加深理解,这些示例使深度学习的复杂性易于理解。

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Neural networks with at least two hidden layers are called deep networks. Recent developments in AI and computer programming in general has led to development of tools such as Tensorflow, Keras, NumPy etc. making it easier to model and draw conclusions from data. In this work we re-approach non-linear regression with deep learning enabled by Keras and Tensorflow. In particular, we use deep learning to parametrize a non-linear multivariate relationship between inputs and outputs of an industrial sensor with an intent to optimize the sensor performance based on selected key metrics.

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Neural networks with at least two hidden layers are called deep networks. Recent developments in AI and computer programming in general has led to development of tools such as Tensorflow, Keras, NumPy etc. making it easier to model and draw conclusions from data. In this work we re-approach non-linear regression with deep learning enabled by Keras and Tensorflow. In particular, we use deep learning to parametrize a non-linear multivariate relationship between inputs and outputs of an industrial sensor with an intent to optimize the sensor performance based on selected key metrics.

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