Join thousands of AI enthusiasts and experts at the Learn AI Community.

Publication

Latest

Why Python?

Last Updated on June 21, 2022 by Editorial Team

Author(s): Tanish Raja

Originally published on Towards AI the World’s Leading AI and Technology News and Media Company. If you are building an AI-related product or service, we invite you to consider becoming an AI sponsor. At Towards AI, we help scale AI and technology startups. Let us help you unleash your technology to the masses.

In present times, if you know Python, you are already a millionaire!

Photo by Clément Hélardot on Unsplash

What is Python?

  1. It is one of the most popular languages used worldwide and has seen exponential growth over the past few years.
  2. It is the fastest-growing programming language in the world. Python is an interpreted language, and one of the main reasons for its popularity is that it is the most straightforward programming language; literally, anyone can learn Python regardless of their career background.
  3. It is a highly versatile programming language with numerous applications. For instance, we can use it in AI, Machine Learning, Data Science, Data Mining, Data Analysis, Web Development, Testing, Automation Scripting, and the list goes on.
  4. It is a highly scalable language used by the world’s largest companies like Google, Amazon, Facebook, Spotify, Netflix, and many more.

Moreover, Python has various excellent libraries and frameworks that save time and effort. Some of the popular libraries are:

· NLTK for natural language processing

· Scikit-learn for machine learning applications

· Matplotlib for plotting charts and graphs

· SciPy for science, mathematics, and engineering applications

· NumPy for scientific computing

· Django for server-side web development

· BeautifulSoup for HTML parsing and Web Scraping

Let’s have a look at a simple example to understand the simplicity of Python code as compared to other programming languages such as C and Java.

C Program to print “Hello World” :

#include <stdio.h>
void main()
{
printf(“Hello World”);
}

Java Program to print “Hello World” :

public class HelloWorld{
public static void main(String []args){
System.out.println(“Hello World”);}}

Python program to print “Hello World” :

print(‘Hello World’)

So, the above examples clearly show us the simplicity and straightforwardness of the Python programming language. Python is designed to remove the unnecessary and keep only what is necessary. As a result, Python is easier to read, write, and learn than most other major programming languages.

To understand more about this programming language, let’s glance briefly at some of its Use Cases.

Use Cases of Python Programming Language:

Data Analysis:

Data is the new currency. Everything is about data. When you are connected to the virtual world, there are tons and tons of data available which can be used in ways one cannot even think of. Unfortunately, the majority of the data is erroneous, which means that the data is unclear, and has some noise or missing values. To perform any kind of analysis, it is very important to clean the data by applying some preprocessing techniques. This can be done by using various Python libraries like NumPy, Pandas, etc. We can also use MatplotLib and Seaborn to visualize the data. Other than that, to perform scientific computations, we can use SciPy and Scikit-Learn libraries. Once the data is clean, it can be further analyzed to reach some meaningful conclusions. More and more companies are moving toward Data-driven decision-making rather than relying on human instincts. For instance, an e-commerce website can perform data analysis to know which product is their best-selling product and vice-versa or which product leads to maximum profitability for the company, and many more results/conclusions can be drawn through it.

Web-Scraping:

This technique is also known as web-data mining. As the name clearly suggests, Web scraping is an automatic method to extract large amounts of data from websites. Again, most of the data extracted are unstructured and need to be converted into a structured format for further analysis. It is a technique to facilitate information retrieval, which helps in gathering information from multiple sources into a single entity. The scraper mainly performs 3 steps: it draws the desired links from the web, the data is extracted to get the data from the source links, and finally, the data is saved in a readable file for further analysis. Moreover, real-time analysis is also an important function that Python provides. When it comes to price comparison, inventory tracking, and other similar tasks, real-time data scraping is critical. The data can change in the blink of an eye, resulting in massive capital gains for a company. The scraper must constantly monitor the websites and scrape data. Python has multiple libraries, frameworks, and tools to perform scraping such as BeautifulSoup, Scrapy, Selenium, etc.

Data Science (Artificial Intelligence and Machine Learning):

Python is a go-to language for any Data Scientist, obviously because of its simplicity and resourceful collection of libraries/packages used to implement various AI and ML models such as SciPy, Scikit-learn, Pandas, Seaborn, TensorFlow, Keras, NumPy, etc. Using these packages, a variety of AI/ML tasks such as Image Recognition, Content generation, and Model prediction can be performed. For instance, based on a customer’s search pattern recommendations can appear based on their interests. More importantly, Python can also aid in Health prediction; various Machine Learning models can be trained using Python to predict diseases like Diabetes, Heart-related diseases, Chronic Kidney Disease, and Parkinson’s Disease prediction. After training the ML models, they are validated using a test dataset, and then the accuracy is calculated based on that; this can also help in reducing the number of False negatives, which is an essential aspect in the field of medical science.

Software Development:

Python is widely used in the field of software development. Python packages and applications are intended to make the software development process easier. For example, the Dropbox desktop application is entirely built-in Python language, and the majority part of the Spotify application is also developed using the same. Furthermore, different types of companies use Python as a platform to build their in-house software/tools. Moreover, Python is not just limited to this; it is also used in software testing, building control, and many other ways by the developers.

Web Development:

Python is also one of the most critical languages for Wed Development. Many websites we use daily are developed using Python and its frameworks like Django and Flask. These Python Web-Frameworks include built-in libraries that simplify tasks like content management, database interaction, and interfacing with various internet protocols like HTTP, IMCP, SMTP, FTP, etc.. For instance, web applications like Netflix, YouTube, Facebook, and Quora are majorly built using Python. Surprisingly, web applications like Reddit and Instagram are completely developed using Python Programming Language.

Finally, the above-mentioned are just a few of them, if not infinite; Python has many Use-Cases.

Conclusion:

So, this blog shows how Python Programming is dominant in the world of technology. It also shows how easy it is to write code in Python compared to other programming languages. Please let me know if you have any questions regarding this blog. Also, let me know which topics you would like me to cover in my future blogs. Thanks for reading.

References:

https://www.dataquest.io/blog/real-world-python-use-cases/

https://levelup.gitconnected.com/5-python-use-cases-that-only-a-few-programmers-know-35e25ddf13d4

https://www.upgrad.com/blog/python-applications-in-real-world/


Why Python? was originally published in Towards AI on Medium, where people are continuing the conversation by highlighting and responding to this story.

Join thousands of data leaders on the AI newsletter. It’s free, we don’t spam, and we never share your email address. Keep up to date with the latest work in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.

Published via Towards AI

Feedback ↓