Artificial intelligence (AI) is a term to describe a branch of computer science that is dedicated to creating intelligent machines that would learn to work and react like humans. The field of Artificial Intelligence is not limited to creating only high levels of machine learning, but also to utilize data input in a manner required to produce a needed result. AI has multiple varieties and characteristics. Some of these types are noted as follows.
In this tutorial, we will consider how to enable both Python 2 and Python 3 for use on CentOS 8. In earlier distributions of CentOS, an unversioned Python command was available by default.
When the CentOS installation was complete, it was possible to drop into a Python shell by simply running the “python” command in a terminal.
Paradoxically, CentOS 8 does not have an unversioned Python command by default. This begs the question, why? RedHat states that this choice is by design “to avoid locking users into a specific version of Python.” Currently, RedHat 8 utilizes Python 3.6 implicitly by default, although Python 2.7 is additionally provided to maintain existing software.
In this tutorial, we are going to take a look at how to get started with TensorFlow on CentOS. We will be covering two methods. First, we will take a look at installing TensorFlow in a Python virtual environment via the Python package manager pip. After that, we will walk through installing TensorFlow via the Anaconda package manager. Finally, we will cover building a TensorFlow pip package from source.
In this tutorial, we are going to cover how to set up a Python virtual environment on CentOS. A Python virtual environment makes it possible to install Python packages into a discreet Python ecosystem that is entirely separate from your system’s default Python framework. This means that you do not have to worry about overwriting the installation of any current packages that might be defaulted to the existing version of Python on your system.
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