Niranjan Kumar is working as a Senior Consultant Data Science at Allstate India. He is passionate about Deep Learning and Artificial Intelligence. He writes about the latest tools and technologies in the field of Deep Learning. He is one of the top writers in Artificial Intelligence at Medium. A Graduate of Praxis Business School, Niranjan Kumar holds a degree in Data Science. Feel free to contact him via LinkedIn for collaboration on projects
Recurrent Neural Networks(RNN) are a type of Neural Network where the output from the previous step is fed as input to the current step. In the case of Convolution Neural Networks (CNN), the output from the softmax layer in the context of image classification is entirely independent of the previous input image.
In this blog post, we will discuss how to build a Convolution Neural Network that can classify Fashion MNIST data using Pytorch on Google Colaboratory. The way we do that is, first we will download the data using Pytorch DataLoader class and then we will use LeNet-5 architecture to build our model. Finally, we will train our model on GPU and evaluate it on the test data.
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