Machine learning projects are what the future is looking for, better personalization, more innovative recommendations, and improved functionality. Now, the obvious question is- what programming language should be used for Machine Learning projects? Here, we will explain why you should consider using Python for Machine Learning in 2021!

Python & machine learning!

Python Software Foundation explains it as a high-level, interpreted, and object-oriented programming language that helps you connect with the computer in their language.

In recent times, Python has been widely used across sectors. BuiltWith states that almost a million websites use Python, and it is a preferred choice for most companies indulged with AI and Machine Learning. From tech giants like NASA, Google and Facebook to service providers like Uber and Netflix, all the industry’s big players use Python.

Want to know why Python is the best technology for machine learning projects? Well! There’s not a single reason but many! Let’s explore why Python is the best option for Machine Learning Projects in 2021!

Why has python is the best option for machine learning projects?

Python provides and lets coders explore all of this because Python is stable, flexible, and has tools that make it super compatible. There are some significant reasons which are indulged in the popularity of Python in the new coding industry:

Simple and consistent

Python assists developers in framing readable and concise code; instead of typical workflows and algorithms behind machine learning. Python lets coders frame that straightforwardly and effectively.

Rapid development

With quick prototyping capabilities, Python is always admired by users. It allows the developers to create programs within a short period compared to the other programming languages. One major reason behind this rapid development is that the language is quite similar to English; developers take less time to read and write it.

Readability

Most programming languages look so complex that most people lose the motivation to learn them during the very first session only! But this is not the case with Python. When it comes to readability, Python is a game changer!

As it resonates with English, it is considered the best readable programming language of all. It is easy to read that developer joining in the middle of the projects can also understand it with no major challenges.

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Extensive selection of libraries and frameworks

Implementing ML algorithms can sometimes be tricky and take a lot of time to frame some proper extensions. Python offers a rich set of libraries that developers can use to enhance an app’s functionality.

Some widespread libraries are:

  1. Scikit-learn for handling algorithms like clustering, linear, and regressions.
  2. Pandas for high-level data structures and analysis. It allows merging, and filtering of data.
  3. TensorFlow for working with deep setting up, training, and utilizing neural works with datasets.

It is vital to have a tested and well-framed environment to assist developers in writing the best codes. To reduce the framing time, coders take access to Python frameworks and libraries. Some of them are Keras, TensorFlow, and Scikit-learn for machine learning.

Platform independent

Platform Independence allows coders to implement things on one machine and can be used on another device without making any changes. Python is platform-independent and supports different platforms such as macOS, Windows, and Linux.

This in-dependency and fluidity make the programmers attract and roam around Python. This is a platform that makes training a lot cheaper and more accessible.

Great community and popularity

In the last survey by Stack Overflow, Python was among the top 5 programming languages. In the first place, web development prevails, accounting for about 26% of the used cases. If we combine data science and machine learning, that will account for 27%.

Low entry barrier

Working for Machine Learning means dealing with many data most conveniently and effectively. The simplicity of the syntax reduces the complexity of the systems and ensures clear relations between the system elements.

Visualization options

Last but not least, data visualization plays a major role in Machine Learning. And the kind of visualization options we get in Python is effective, and it allows the developers to quickly build histograms, charts, and plots for better understanding.

Hope now you are aware of what makes Python best for ML in 2021! As mentioned earlier, Python has been in the game for a long time. Considering how it complements technologies, like machine learning and artificial intelligence, we can say Python will stay in the competition!

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