A Practical Example of Character Level Text Generation with Tensorflow. Today, we will provide a walkthrough example of how you can apply character-based text generation using RNN and more particularly GRU models in TensorFlow
Today, we will provide a walkthrough example of how you can apply character-based text generation using RNN and more particularly GRU models in TensorFlow. We will run it on colab and as training dataset we will take the “Alice’s Adventures in Wonderland”. In another post we explained how you can apply word-based text generation. Feel free to compare the two approaches.I wrote this article after finishing the course Natural Language Processing in Tensorflow by Coursera and deeplearning.ai.
Keras vs Tensorflow - Learn the differences between Keras and Tensorflow on basis of Ease to use, Fast development,Functionality,flexibility,Performance etc
In this article, I’ll walk you through my experience to code a model that will learn some Ed Sheeran songs and try to create some first sentences for a song.
This video on TensorFlow and Keras tutorial will help you understand Deep Learning frameworks, what is TensorFlow, TensorFlow features and applications, how TensorFlow works, TensorFlow 1.0 vs TensorFlow 2.0, TensorFlow architecture with a demo. Then we will move into understanding what is Keras, models offered in Keras, what are neural networks and they work.
We will go over what is the difference between pytorch, tensorflow and keras in this video. Pytorch and Tensorflow are two most popular deep learning frameworks. Pytorch is by facebook and Tensorflow is by Google. Keras is not a full fledge deep learning framework, it is just a wrapper around Tensorflow that provides some convenient APIs.
Natural Language Processing (NLP) has hit an inflection point, and this talk shows you how TensorFlow and Keras make it easy to preprocess, train, and hypertune text models.