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Voltar para Visualizing Filters of a CNN using TensorFlow

Comentários e feedback de alunos de Visualizing Filters of a CNN using TensorFlow da instituição Coursera Project Network

42 classificações
3 avaliações

Sobre o curso

In this short, 1 hour long guided project, we will use a Convolutional Neural Network - the popular VGG16 model, and we will visualize various filters from different layers of the CNN. We will do this by using gradient ascent to visualize images that maximally activate specific filters from different layers of the model. We will be using TensorFlow as our machine learning framework. The project uses the Google Colab environment which is a fantastic tool for creating and running Jupyter Notebooks in the cloud, and Colab even provides free GPUs for your notebooks. You will need prior programming experience in Python. This is a practical, hands on guided project for learners who already have theoretical understanding of Neural Networks, Convolutional Neural Networks, and optimization algorithms like gradient descent but want to understand how to use the TensorFlow to visualize various filters of a CNN. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....
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1 — 4 de 4 Avaliações para o Visualizing Filters of a CNN using TensorFlow

por Kenneth N

4 de jul de 2022

very well prepared and explained. but colab is slow

por Pooja.Bidwai p

14 de dez de 2021


por Fabian B

14 de abr de 2022

instructor explains everything clearly, but an actual application was missing. a quick cats and dogs comparison on how to infer filter activation would have been helpful.

por Javier G

24 de mai de 2022