Introduction
Keras is an open-source software library that provides a Python interface for artificial neural networks. Keras acts as an interface for the TensorFlow library.
It is a neural network library based on the Python programming language designed to simplify machine-learning applications. Keras runs on top of frameworks such as TensorFlow.
So In this guide, we will show you how to install Keras on Ubuntu systems.
Installation
Keras is built to work with many different machine learning frameworks, such as TensorFlow, Theano, R, PlaidML, and Microsoft Cognitive Toolkit. However, the best framework to use with Keras is TensorFlow.
Also you can follow the steps on the installing guide of TensorFlow from this Link Install Tensorflow on Ubuntu.
After you successfully install Tensorflow, just follow the steps below to install Keras.
Install Keras
- Install keras with the following command
pip3 install keras
- Verify the installation by displaying the package information by running the below command with pip.
pip3 show keras
Keras vs. TensorFlow
So Keras and TensorFlow are both open-source software.
TensorFlow is a software library for machine learning.
Keras runs on top of TensorFlow and expands the capabilities of the base machine-learning software.
Also Keras makes implementation, testing, and usage more user-friendly.
Keras works with TensorFlow to provide an interface in the Python programming language. It works by using layers and models.
Layers
A layer is a processing unit. It accepts input, performs computations on that input, then outputs the transformed information.
A layer requires the following:
- Shape of input: Defines how the layer will make sense of the input information
- Initializer: Sets the weight, or importance, of each piece of information.
- Activator: Transforms the data into a non-linear form.
Models
A model is a group of layers. A model also includes training and inference modules – this is where machine learning comes into play. Each model has the following:
- Inputs: Scripts that send information into the Keras model.
- Outputs: The information that comes out after being transformed by the Keras model.
- Type: A model may be sequential, meaning that it is built one layer at a time to solve a problem. Or, it can be functional, where layers may interconnect in complex and non-linear ways.
Conclusion
In this tutorial, we illustrated how to install Keras and Tensorflow on Ubuntu Linux system with the necessary Python packages.
