There has been a constant that is happening rapidly since the early 90s at least on the consumers’ end. Initially, there were websites that were being used. By the side, there were companies who were working on software. But later on, when the smartphone market rose, there was a lot that was going on. There was a lot of fight in order to make the entire process of implementing and conceiving on app features automated. Also, App features that can provide recommendations based on acute data analysis.
These systems were capable of suggesting you goods just like your best friend. Although different programming languages were used for its implementation, and Python actually got popular and is still among the top contenders in case of machine learning. Therefore, in order to further explore this topic read down the article.
Introduction to Python Language
A lot of people believe that it is a much recent language. Although, the language was first released in the year 1991. It was when the work in the direction of machine learning started to take up the pace that it became so popular. Python was created by Guido Van Rossum. It is a high-level, interpreted, general-purpose language that is widely being used in today’s scenario because of its application.
The interpreters that are used for the language are available for multiple Operating Systems. A non-profit organization known by the name Python Software Foundation is the one that manages and directs all the resources of Python. Also, if we talk about the development then a community of developers do it that are globally situated. They maintain CPython which is an open-source reference implementation for the language.
Uses of Python:
- Web and App Development: Why can it be used for these efficiently? The answer is simple: the language supports multiple frameworks, micro-frameworks, and libraries. This makes development easier in many sorts.
- Education: Well, there is no doubt that C and C++ are excellent languages, to begin with. Although, Python is relatively easy to learn and also quite modern which means it can be a great language to start learning to program. There is also a lot of material that is available online for anyone to begin with.
- Software Development: It is more commonly known as a support language. This is the reason it is used by multiple developers to control the build and manage & test using different methods.
- GUIs for Desktop: It may not be something that is often heard. Although, Python is a great tool for doing so. The TKinter GUI library can be found easily with most of the binary distribution of the language. Both Python and Tkinter make the development of any GUI very fast and easy.
- Business Application: Well, if you wish to seek the language for business purposes then it surely doesn’t disappoint. It is used quite often for the development of ERP systems and E-Commerce websites. It supports Odoo which is a suite for complete enterprise management applications. Also, Tryton which is a general-purpose application platform.
Reasons why it is so widely accepted?
Easy to Use: Well in general if you are just learning python as a beginner language then it may be a little difficult. Although, if you already have a programming background and have had experience with some other language, you might find Python relatively quite easy. One good reason for that is the syntax. The syntax of python is quite easy to nail and since Python opted to get rid of more trivial issues. For instance, usage of semicolons, unnecessary parenthesis, datatype declaration etc. The language can save you loads of lines in comparison to some other language. It is also highly effective and much easier to build complex software.
Wide Support to Libraries and Frameworks: One of the major reasons why Python is preferred over multiple languages is because of its libraries and frameworks. If you wish to know about all the modules of the python language then click on the link here. All of these can be used for development purposes. Below are some of the major libraries and frameworks because of which Python is so widely accepted.
- NumPy: This one allows you to use high-level mathematical functions applied to your programming. If you have a requirement for using multi-dimensional arrays and matrices then this library of python can be your rescue.
- Pandas: Pandas is closely related to NumPy since it lets you apply the data structure which is known as Data Frames. Developed by Wes McKinney, Pandas is a high-level data manipulation tool. This one allows you to manipulate the tabular data to be processed easily.
- Seaborn: This is a highly effective tool that is used for the statistical representation of data.
- SciKit Learn: This is the most important aspect of this article. It is the machine learning library which enables everything for the people to apply. It is free in nature and can be used for regression, classification, and clustering algorithms. It can be easily used alongside NumPy and Pandas. If you are into machine learning then this is the library you need to nail.
It is one part of machine learning which has its unique application. These systems are inspired by the brain of humans and animals for learning. In this, the machine learns things by getting task-oriented rules. One of the best examples for this would be image recognition. Python supports multiple tools to help you with that. Although below I will mention only the most popular.
- TensorFlow: It is a free and open-source library that can be used for dataflow and differential programming. This one is a mathematical library that can be for creating complex neural networks. It was developed by Google Brain which is a research team of Google. Later on, the library was made opensource in the year 2015.
Community and Support:
Backed by one of the best tech company Google, there is no doubt that the language has great support. Apart from that, there are various forums, websites, and video tutorials that are discussing and teaching Python. This creates a much inclusive environment for the language to be taken seriously.
So this was our take on why Python is so widely accepted for Machine Learning. Although, this doesn’t mean that it is a superior language to any other. Some languages are capable of doing something while others are capable of doing something else. Therefore, it is completely up to the developers to decide what they go for. We are Agicent Technologies and we are very happy to have this opportunity to write for Emizen Tech Pvt Ltd.. We hope this article may have been of some help to you. Also, thank you for reading it until the end.