Dynamic Recurrent Neural Network (LSTM) ( notebook).Build a bi-directional recurrent neural network (LSTM) to classify MNIST digits dataset, using TensorFlow 2.0+ 'layers' and 'model' API. Bi-directional Recurrent Neural Network (LSTM) ( notebook).Build a recurrent neural network (LSTM) to classify MNIST digits dataset, using TensorFlow 2.0 'layers' and 'model' API. Recurrent Neural Network (LSTM) ( notebook).Raw implementation of a convolutional neural network to classify MNIST digits dataset. Convolutional Neural Network (low-level) ( notebook).
Use TensorFlow 2.0+ 'layers' and 'model' API to build a convolutional neural network to classify MNIST digits dataset.
#Tensorflow neural network tutorial how to
Very simple example to learn how to print "hello world" using TensorFlow 2.0+. Update (): Moving all default examples to TF2. Besides the traditional 'raw' TensorFlow implementations, you can also find the latest TensorFlow API practices (such as layers, estimator, dataset. It is suitable for beginners who want to find clear and concise examples about TensorFlow. For readability, it includes both notebooks and source codes with explanation, for both TF v1 & v2.
This tutorial was designed for easily diving into TensorFlow, through examples.