Tag: Framework

What is PyCharm?

PyCharm is an IDE (or Integrated Development Environment) for the Python programming language. It is a cross-platform development environment that is compatible with Windows, macOS, and Linux. It provides a tool that integrates code analysis, graphical debugging, unit testing, and also contains an integrated terminal that supports development on remote hosts and virtual machines.

Keras is a Python-based high-level neural networks API that is capable of running on top TensorFlow, CNTK, or Theano frameworks used for machine learning. It can be said that Keras acts as the Python Deep Learning Library. Keras was created with emphasis on being user-friendly since the main principle behind it is “designed for human beings, not machines.” The core data structure of Keras is a model, or a way to organize layers.

Today we’re going to install Ruby on Rails using RVM (the Ruby Version Manager) onto a CentOS 8 server. Let's start by defining a few terms and definitions we will be using during the process.

With the constant technological development we are witnessing in the world of hosting, it is necessary to familiarize ourselves with the terminology and meaning of the systems we are using. An important distinction that we need to make is between virtual machines and containers, as they are both widely used in the hosting industry, and yet they are often confused.

Intro 

In the last tutorial, we learned how to install Vue 3 CLI and gone over a few of the new features which were shipped with it. 

In this article, we will go over two features that are really something new in the world of JavaScript Frameworks. These features are Plugins and Graphical User Interface. 

In this tutorial, we are going to set up TensorFlow in a virtual Python environment on Ubuntu 18.04. TensorFlow is an open-source framework, developed by the Google Brain team, designed to be a high-level interface for implementing machine learning and mathematical operations. This library provides developers an avenue to work on complex projects like neural networks through an easy to use Python API. One of the significant benefits of having a Python front-end is that it is portable between operating systems like Linux and Windows.