This tutorial walks through the installation of Keras, basics of deep learning, Keras models, Keras layers, Keras modules and finally conclude with some real-time applications.

Using Keras model, Keras Layer, and Keras modules, any ANN algorithm (CNN, RNN, etc.,) can be represented in a simple and efficient manner. The following diagram depicts the relationship between …

Keras is compact, easy to learn, high-level Python library run on top of TensorFlow framework. It is made with focus of understanding deep learning techniques, such as creating layers for neural …

As learned earlier, Keras layers are the primary building block of Keras models. Each layer receives input information, do some computation and finally output the transformed information.

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This tutorial is prepared for professionals who are aspiring to make a career in the field of deep learning and neural network framework. This tutorial is intended to make you comfortable in getting started …

Keras is based on minimal structure that provides a clean and easy way to create deep learning models based on TensorFlow or Theano. Keras is designed to quickly define deep learning models.

import keras from keras. datasets import mnist from keras. models import Sequential from keras. layers import Dense, Dropout, Flatten from keras. layers import Conv2D, MaxPooling2D from keras import …

As learned earlier, Keras layers are the primary building block of Keras models. Each layer receives input information, do some computation and finally output the transformed information.