TensorFlow Tutorial Part1
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This document provides an overview and outline of a TensorFlow tutorial. It discusses handling images, logistic regression, multi-layer perceptrons, and convolutional neural networks. Key concepts explained include the goal of deep learning as mapping vectors, one-hot encoding of output classes, the definitions of epochs, batch size, and iterations in training, and loading and preprocessing image data for a TensorFlow tutorial.
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