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Deep Learning - Cours 2 [June 3, 2020]


In this second video in the series, Dr. Bernard Giusiano, building on the concepts introduced in the "Deep Learning - Cours 1", explores certain more avanced aspects of deep learning. The choice of  hyperparameters is presented and a number of different neural network architectures, such as Convolution Networks, Autoencoders and Recurrent Networks, are introduced. Bernard also gives examples of tools and platforms available to those wishing to explore or create their own deep learning networks. 

Tags: apprentissage profond architecture hyperparametres reseaux convolutifs reseaux de neurones reseaux recurrents



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