Patents

This tutorial is for the beginners in deep learning and TensorFlow. The main objective of the tutorial is to help the beginners write their own TensorFlow programs by introducing reference program examples from the basic concept to the advanced network architectures. Topics include primitive TensorFlow data structures such as variables, placeholders, tensors, and matrices; implementation skills for graph building, network layers, loss function design, and training algorithms; basic neural network architectures; convolutional neural networks (CNNs) with MNIST and CIFAR10 examples; advanced architectures including AlexNet and VGGNet; recurrent neural networks (RNNs) with text processing examples; extra implementation tips....