Build a FC layer‐based neural network to recognize hand‐written digits
$30-250 USD
Bezahlt bei Lieferung
Train and test a neural network for entire MNIST hand‐ written digit dataset. Some information of the network is as follows:
-Its structure is 784‐200‐50‐10. Here 784 means the input layer has 784 input neurons. This is because each image in MNIST dataset is 28x28 and you need to stretch them to a length‐784 vector. 200 and 50 are the number of neurons in hidden layers. 10 is the number of neurons in output layer since there are 10 types of digits.
-The two hidden layers are followed by ReLU layers.
-The output layer is a softmax layer.
Use a deep learning framework to train and test this network.
For dataset loading in Pytorch, you can refer to the following example code: [login to view URL] (feel free to use tensor but I’m not sure how you would go about loading the mnist dataset)
I've included a py file to download the MNIST database if you need it
Projekt-ID: #24855675
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