Keras

In this chapter, we will learn about the Keras pre-trained models . Let us begin with VGG16. VGG16 VGG16 is another pre-trained model. It is also trained using ImageNet. The syntax…

ResNet is a pre-trained model. It is trained using ImageNet. ResNet model weights pre-trained on ImageNet. It has the following syntax − keras.applications.resnet.ResNet50 ( include_top = True, weights = 'imagenet', input_tensor = None,…

Keras applications module is used to provide pre-trained model for deep neural networks. Keras models are used for prediction, feature extraction and fine tuning. This chapter explains about Keras applications…

This chapter is about Keras - Time Series Prediction using LSTM RNN. In this chapter, let us write a simple Long Short Term Memory (LSTM) based RNN to do sequence…

This topic is about Keras - Regression Prediction using MPL. let us write a simple MPL based ANN to do regression prediction. Till now, we have only done the classification…

This topic is about Keras - Convolution Neural Network. Let us modify the model from MPL to Convolution Neural Network (CNN) for our earlier digit identification problem. CNN can be represented as…

This chapter deals with the model evaluation and model prediction in Keras. Let us begin by understanding the model evaluation. Model Evaluation Evaluation is a process during development of the…

This chapter is about Keras Model Compilation. Previously, we studied the basics of how to create model using Sequential and Functional API. The compilation is the final step in creating…

This topic is about Keras Models.As learned earlier, Keras model represents the actual neural network model. Keras provides a two mode to create the model, simple and easy to use Sequential…

Keras allows to create our own customized layer. Once a new layer is created, it can be used in any model without any restriction. Let us learn how to create…