While creating a Sequential model in Tensor flow and Keras is not too complex, creating a residual network might have some complexities. In this article, I show you how to create a residual network from scratch. How to Create a Residual Network in TensorFlow and Keras. The code with an explanation is available at GitHub.
ResNet, was first introduced by Kaiming He. If you are not familiar with Residual Networks and why they can more likely improve the accuracy of a network.
While creating a Sequential model in Tensor flow and Keras is not too complex, creating a residual network might have some complexities. In this article, I show you how to create a residual network from scratch.
Keras with TensorFlow Course - Python Deep Learning and Neural Networks for Beginners Tutorial: How to use Keras, a neural network API written in Python and integrated with TensorFlow. We will learn how to prepare and process data for artificial neural networks, build and train artificial neural networks from scratch, build and train convolutional neural networks (CNNs), implement fine-tuning and transfer learning, and more!
Training Neural Networks for price prediction with TensorFlow: Learn how to make your DNN more efficient in solving regression problems: a practical guide with TensorFlow and Keras.
This chapter continues the series on Bayesian deep learning. In the chapter we’ll explore alternative solutions to conventional dense neural networks.
A practical and hands-on example to know how to use transfer learning using TensorFlow. We will learn how to use transfer learning for a classification task.