Deep learning is a machine learning methodology that studies networks with many layers. In this tutorial, you will build a neural network with Keras.
Before going forward, you should have some knowledge of the following technologies
The following libraries are required, so ensure that you have them installed:
Installing Keras
To install Keras, use the pip package as follows:
Keras is a high-level Neural network. It makes it possible to implement deep learning models in a fast and efficient way. The simplest model in Keras is known as the Sequential model and is defined as follows.
Keras is a high-level library used to build deep neural networks. When you talk of high-level, it means simplicity and human-readable. You will not dive deep into all the mathematical concepts of neural networks, but you will only focus on building deep learning networks.
Keras makes use of either Tensor flow (by Google) or Theano backend (by Montreal’s Theano) to give it computational capabilities; this means that the Keras library can run on both Tensor flow and Theano frameworks. The choice of which framework to use depends on your taste. However, in this tutorial, you will use Tensor flow as our backend.
Keras has gained popularity over the years because it leverages the use of both Tensor flow and Theano. Other advantages include:
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