What is Python used for?
Python is easy to learn and to use. Its functions can be carried out with simpler commands and less text than most competing languages. And this might explain why it’s soaring in popularity, with developers, coding students and tech companies. know more at Python online training
It’s not an exaggeration to say that Python plays a small part of all of our lives. It’s one of those invisible forces with a presence in our mobile devices, web searches and gaming (and beyond). So it was an obvious choice for inclusion in our full stack coding bootcamp. Here’s an introduction to the language itself, and some of the everyday but profound, things that Python is used for.
Python — an overview
Python was created in 1991 by Dutch programmer Guido Van Rossum. It is an interpreted language. This means that it has an interpreter to execute the programme directly, as opposed to depending more complicated machine languages. In fact, Van Rossum wants Python to eventually as understandable and clear as plain English. He has also made the language open source, which means that anyone can contribute to it, and he hopes that it will become as powerful as competing languages.
1. Python for data science
The first — and perhaps today’s most talked about use of Python — is in data science. Data science is the practice of extracting information and insight from data. In this case, data science includes machine learning, data visualization and data analysis.
Python for machine learning
Machine learning (ML) is an application of artificial intelligence (AI) where machines learn from programs without being explicitly programmed to do so. In essence, machine learning enables computers to program themselves. Examples of ML algorithms include:
- Recommender systems — for example, when Netflix or Youtube makes recommendations based on your watch history.
- Image recognition systems — for example, that can recognize whether an image is a cat or dog, the popular from the TV series Silicon Valley, or by Apple that recognizes you unlocks your phone.
Why Python for machine learning
Since its early days, Python has been used for scientific and numerical computing. Because machine learning is mainly numerical computation, Python is extremely useful for ML.
Especially with the introduction of the largest end-to-end ML platform developed by Google, Python has become the de-facto language for ML applications. , another deep learning platform started by Facebook, is also gaining popularity. know more at python training
Additionally, Python comes with a simple and easy to use ML package that can get you started very easily in Machine Learning. You can see the increase of popularity in these ML platforms in the graph below.
Applications of Python
Web Development
While HTML, CSS, and Javascript may be the common choice of tools when it comes to web development, Python is also a great choice.refers to the building of websites on the internet, from static, plain text pages to dynamic ecommerce sites and interactive internet applications. know more at python online training
Coding is crucial in web development to build out site functions, optimize user experience, and ensure that that information is organized properly. Python’s web frameworks such as Django and Flask have become popular options for website development.
Python is a great option for backend web development, and is used by many companies today.
These open-source frameworks allow users to build web applications more efficiently due to Python’s ability to handle vast amounts of data and automate tasks. In fact, companies such as Instagram, Pinterest and Google incorporate Python in their
Data Science
Python is also a major language of choice when it comes toand data analysis.
In the age of big data, we come into contact with data frequently in our everyday lives, with technology such as navigation (GPS), online shopping, energy use, and wearables such as smart watches.
The average household contains around and that number is likely to increase in the future! With so many devices, there is a vast amount of data that businesses need to process in order to provide their services.
Python-based tools are often used to visualize, process, and analyze large amounts of data.
Data science relates to processing data and inferencing trends — and Python is incredibly useful in this area due its intensive packages like scipy, numpy, and pandas.
Additionally, the matplotlib package can be used to build data visualizations. This makes Python a popular choice in fields like bioinformatics that also involve a lot of data and modeling.
