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There are three routes you can go with this. The simplest would probably be to use Microsoft's Face API, which is part of their Azure Cognitive Services platform. All of the computing is done in the cloud, and at least for your purposes, the modelling necessary to detect faces has already been performed by Microsoft, so it's a single method call to send it a picture and receive back a bounding box. The caveat is... Source: over 1 year ago
Azure Cognitive Services provide a few interesting AI as a service offerings beyond CLU & LUIS that can be helpful for conversational AI:. - Source: dev.to / over 1 year ago
Hello, not sure about the quality of this API as I’ve just heard about it but thought it might help you: Azure Cognitive Services. Source: over 1 year ago
Cognitive Services Https://azure.microsoft.com/en-us/services/cognitive-services/. - Source: dev.to / almost 2 years ago
Microsoft Azure offers an umbrella service known as Cognitive Services. This service provides AI capabilities that you can integrate into your existing applications through a single managed area. - Source: dev.to / about 2 years ago
Converting the images to a tensor: Deep learning models work with tensors, so the images should be converted to tensors. This can be done using the to_tensor function from the PyTorch library or convert_to_tensor from the Tensorflow library. - Source: dev.to / about 1 year ago
So I went to tensorflow.org to find some function that can generate a CSR representation of a matrix, and I found this function https://www.tensorflow.org/api_docs/python/tf/raw_ops/DenseToCSRSparseMatrix. Source: almost 2 years ago
Can anyone offer up an explanation for why there is a performance difference, and if possible, what could be done to fix it. I'm using the installation guidelines found on tensorflow.org and installing tf2.7 through pip using an anaconda3 env. Source: almost 2 years ago
I don't have much experience with TensorFlow, but I'd recommend starting with TensorFlow.org. Source: about 2 years ago
I have looked at this TensorFlow website and TensorFlow.org and some of the examples are written by others, and it seems that I am stuck in RNNs. What is the best way to install TensorFlow, to follow the documentation and learn the methods in RNNs in Python? Is there a good tutorial/resource? Source: about 2 years ago
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Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.