Table of Contents
Python Introduction
A simple question, what is Python used for? we will try to find out here. Python is an Interpreted Programming language. Python is known as an interpreted language because it uses an interpreter to translate the code and makes it computer understandable.
Guido Van Rossum, a Dutch programmer, founded Python in 1991. Python is used in many fields like web development, Artificial intelligence, machine learning, data science, etc. we will discover much more about how all these fields use Python and we will also discuss some interesting facts about Python.
Here is a list of some areas where Python is used by many institutes.
- Web Development
- Data Science and Data Visualization
- Artificial Intelligence
- Machine Learning
- Game Development
- Scientific and Numeric Applications
- Desktop GUI
- Software Development
- Operating Systems
How Python is used in web development?
Python is used in writing web applications. This is possible with the help of different Python web development frameworks. The frameworks include Django, Flask, Web2py, CherryPy, TurboGears, Bottle, Grok, and much more.
A popular example is Django. It is a popular framework for web development. It uses Python as a programming language and maintained by Google. Here is an introductory video by Django CMS.
Python has a lot of options for web development:
How Python is used in Data Visualization?
Data visualization is critical for better understanding data and uncovering secret insights. Matplotlib is the most simple and widely used visualization library in Python.
The following are the most widely used Python libraries for Data visualizations:
1. Matplotlib
2. Seaborn
3. Plotly
4. Bokeh
4. Ggplot
Matplotlib is a Python library that allows you to create static, animated, and interactive visualizations.
Seaborn is a matplotlib-based Python data visualization library. It has a high-level GUI for creating visually appealing and insightful statistical graphics.
Plotly develops and maintains the industry’s leading data visualization and user interface software for machine learning, data science, engineering, and the sciences. Python, R, Julia, and other programming languages are all supported.
Bokeh is a Python library that allows you to make interactive visualizations for modern browsers. It allows you to create stunning graphics, ranging from basic plots to complex.
How Python is used in AI?
Python is a more common AI language than C++. This is due to the fact that Python is quick to learn and use. They can also be used for data mining because of their various repositories. C++ also produces runtime code that is more compact and faster.
People find Python code to be understandable, making it easier to construct AI models. Python, according to many software developers, is more intuitive than other programming languages.
I’ll show you some of the most common and powerful AI-based Python libraries.
Tensorflow: This Google-developed library is widely used in the development of Machine Learning algorithms and the execution of complex computations involving Neural Networks.
It can be used for a variety of activities, but it focuses on deep neural network training and inference. Tensorflow is a dataflow and differentiable programming-based symbolic math library.
Scikit-Learn is a Python library for teaching and learning. Scikit-learn is a NumPy and SciPy-related Python library. It is regarded as one of the best libraries for dealing with large volumes of data.
Numpy is a Python library that is used to compute science and mathematical data. It support for large, multi-dimensional arrays and matrices. It support for a large number of high-level mathematical functions to work on multi-dimensional arrays.
Theano: Theano is a Python library that allows you to define, optimize, and efficiently evaluate multi-dimensional array-based mathematical expressions. It is based on the NumPy programming language.
Final words about the topic, ” What is Python used for? “
The above statements shows that ” What is Python used for? “.
