7 reasons why should you learn Python - applications of Python

If you are thinking of learning Python or you have just started learning Python you must be wondering what can I use Python for exactly? That's actually a tricky question to ask because there are so many applications of  Python. 



Over time I have seen there are 7 more popular application for Python


  • Web Development
  • Data Science including Machine Learning
  • Data Visualization
  • Scripting
  • Game Development
  • Desktop Application
  • Embedded Application

We will talk about each of the application in detail here - 

1 - Web Development:    
Web frameworks like Django and Flask which are based on Python have recently become very popular for web development. These web frameworks basically help you create server-side code that of course the code that runs on your server as oppose to code that runs on user's devices that is front-end code.

Now you might have questions like:
why web frameworks?
  • Helps build common logic
  • Mapping URLs to Python code
  • Dealing with databases
  • Generating HTML Files 
Which Python Framework I should use Django or Flask?
I would recommend using frameworks according to your need. Like if you have just started learning python you can choose any of them. But for smaller projects use Flask and for bigger and scalable projects use Django.

Flask
  • Fewer components
  • Simpler
  • More Flexible
  • we need to choose which database to use
Django
  • More Components
  • A specific way to deal with databases
  • Choose for straightforward Projects

2 - Data Science and Machine Learning:
Machine learning typically implements algorithms that automatically detects a pattern in the given dataset.
Example: We will give thousands of images of dogs and tables to machine learning algorithm and tell this is the dog and this is the table and algorithm will learn it.
So, when we will give a new image it will recognize. 

We can use the same idea to implement the recommendation system such as youtube, Amazon, and Netflix.

Voice Recognition and Face Recognition are also other application.

Popular Machine Learning Algorithm:
  • Neural Networks
  • Deep Learning
  • Support Vector Machine
  • Random Forest
You can use any of these algorithm to solve image labeling problem explained above.

Popular libraries & Framework for Machine Learning:
  • scikit-learn (Has Built-in algorithms)
  • TensorFlow (low level allows to build algorithm)

3 - Data Analysis and Data Visualization
Let's take an example. Suppose you are working as an analyst at a company and the company sells some products online and as a data analyst if you will see this graph generated using Python -


Data visulalization python


You can come up with following plausible explanation:
  • The product is more popular with men
  • The sample size is too small
  • Men tend to buy this product more only on Sundays

Libraries used for data analysis: Matplotlib & Seaborn

Matplotlib - 

  • One of the most popular
  • Easy to get started
  • Other libraries depend on it

4 - Scripting:
Scripting refers to writing simple programs that are designed to automate simple tasks.

Example: Suppose you have a lot of images and you have to resize them to a particular size. So rather than resizing each image manually, you can write a Python script to resize images.

Python is used for scripting because of:
  • Simple syntax
  • Easy to learn

5 - Game Development:
'Pygame' is the library used for game development in Python.
This is not a very popular game engine. You could use it for a hobby project or for personal project. If you are serious for game development do not use this library.

You can use Unity with C# as it is one of the most popular game engines for game development.



6 - Desktop applications:
 We can create desktop applications using python but Python is not so popular to create desktop application. As most of the developers are using Java, C#, C++. 

Many companies are now using JavaScript as it allows you to get the same code from the website if you have one.

Libraries to create desktop applications using python:

  • Tkinter
  • Qt


7 - Embedded Applications:
Python is also very popular for use in Embedded Systems. Python is used with Raspberry Pi for Embedded Application.




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