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Practical Programming Blog | Tutorials, Resources, Tips & Tricks

What is Python Used For?

Python is one of the world’s most popular programming languages, and for good reason. Hundreds of companies use Python for data science, machine learning, web development, app development, and fintech. Large companies can easily collaborate on projects that are written in Python because it’s easy to read, easy to learn, and its libraries and frameworks make everything more efficient.

Python powers huge social media platforms, recommends your favorite music and movies, powers banking apps, and returns the most relevant websites on your web search. It’s used in industries like retail, e-commerce, fintech, healthcare, political campaigns, and widely popular apps like Instagram and Spotify. 

Data Science

Data Science is used by businesses and researchers alike to find meaningful insights into the numbers. IT, e-commerce, healthcare, news organizations, political campaigns, and more are using data science to maximize their work. 

The most popular and easy tool for this work is Python. Python can be used to process, scrape data from the web, analyze, visualize, and forecast data that is useful to almost anyone in the digital age. Libraries like pandas and Numpy makes data manipulation and predictions easy for new and experienced data scientists alike. BeautifulSoup is a library that executes web scraping. 

Who’s using Python for data science? 

  • Amazon uses Python to analyze customer’s buying habits to recommend products and deals
  • Netflix uses Python to recommend movies, retain customers by making predictions, and even greenlight original productions. 
  • Uber uses Python to calculate ETAs, ride fares, as well as demand and supply

Machine Learning

Machine learning uses data to teach a machine how to make an informed decision based on patterns in datasets. Python can be used for every stage of machine learning from data extraction to the development of complex algorithms. Python’s massive selection of libraries makes machine learning easier than ever. 

With libraries for images, text, audio, data clarification, and deep learning, you won’t have to write every algorithm from scratch to get the incredible benefits of Python for machine learning. Scikit-Learn, Librosa, Seaborn, TensorFlow, and Pytorch will open up the complex insights and automation of machine learning, even for relative beginners.

Who’s using Python for machine learning? 

  • Google uses machine learning in almost everything. Google Translate, Google Search, and Google Photos all run on Python and machine learning. 
  • Facebook uses the Python framework DeepFace for facial recognition to suggest friends to tag in your photos

Web and App Development

Python is a simple and easy way to create websites, web apps, and web platforms quickly. The standard Python library supports HTML so it can be used easily in web development. Plus, frameworks like Django and Flask make it even easier to use for web and app development. 

Flask is a web framework that comes with tools, libraries, and technologies, for building websites, blogs, wikis, and even calendar applications. Django enables the rapid development of secure websites and apps. The Django CRM makes those websites even more robust with simple and secure content management. 

Who’s using Python for web and app development? 

  • Instagram uses Python for its entire application
  • Netflix uses Python to power its recommendation engine
  • Reddit has Python behind almost everything: their core services framework, feature deployment, user authentication, monitoring user activity, and more. 

FinTech 

It’s all about the money in fintech and Python is one of the most cost-effective choices for fintech company’s source code or analysis apps. It’s free and open-source forever. It’s easy to read, easy to learn, secure, versatile, and one of the fastest ways to develop an app. These factors all make Python the most simple, affordable, and secure way to get a fintech app to market efficiently. 

Python’s data science power can be combined with its versatile app development tools to solve some of fintech’s biggest problems. From quantitative problems for pricing, trade management, and risk management platforms. Python can also be used to handle data analytics, regulation, security compliance, and data. 

Who’s using Python for FinTech? 

  • J.P. Morgan uses Python as the core language for their Athena program
  • Bank of America’s Quartz program runs on Python
  • Citigroup’s Analysts and Traders use Python and even teaches Python during their onboarding program for new Analysts
  • Stripe uses Python to develop APIs that integrate their services into websites and mobile apps

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