Machine learning is nothing but using data to make a machine to make intelligent decisions. It is based on recognizing and learning through patterns in data. Intelligent algorithms are then built by extracting, processing, defining, cleaning, arranging and then understanding the data. To perform such tedious tasks, why should one use Python? The answer is simple – It is easy to understand! Adding Python to the implementation process has helped engineers to validate various ideas. and that’s why today DataFlair has come up with a new topic – The importance of Python for Machine Learning.

Before we start with the tutorial, it is recommended to save the link Python Master Guide

Keeping you updated with latest technology trends, Join DataFlair on Telegram

Machine Learning with Python

Consider using Python for machine learning. Now all the questions like- How can these experiences be made real? Or What programming language will be best for this conversion? All of these will vanish away. Python offers all the skillsets that are required for a machine learning or AI project – stability, flexibility and a large number of tools. Python helps developers to be productive and confident about the product that they are manufacturing, from the stages of development to deployment and till the maintenance stage. These add to the popularity of the Python language.

Why Python for Machine Learning?

Below are some of the reasons which will tell you why everyone is using Python for machine learning –

1. Simple and consistent

Python’s simple syntax allows developers to write codes that are reliable, concise and readable. This allows them to only struggle with the solution of the problem and not the code syntax, increasing the productivity of the overall process of development. This simplicity becomes appealing to other developers and urges them to learn python. It’s greater human understanding makes it easier for coders/developers to invent various functional models.

Multiple developments and Collaborative implementation type of projects majorly use Python as the language for code. Prototypes are built faster as the complex machine learning tasks and the testing process can be done quickly. While we find the reason behind greater functionality- frameworks, libraries, and extensions are the reasons that come back as responses.

Now, another reason to learn Python for machine learning is the amazing libraries and frameworks of Python.

2. Libraries and Frameworks

To help developers in the development process, a number of python libraries and frameworks get involved. It is nothing but a pre-written code that can be used to solve a common programming problem. Python has a rich bank of libraries for machine learning, some of them are- TensorFlow, Keras, and Scikit-learn, Numpy, Scipy, Pandas, Seaborn, etc. In these NumPy and Scipy are specifically for scientific and advance computing respectively. Pandas generally used for Data analysis and Seaborn specifically for data visualization. With these pre-defined codes the speed of development increase to an appreciable level.

3. Platform Independence

It basically means one can freely shift from one machine to another without making changes to the actual code (or with minimal changes). This functionality is allowed by python’s framework. This is also one of the keys to the popularity of the python language. It supports many platforms such as- Windows, macOS, and Linux. Most of the companies use their own machine containing powerful GPUs to train their machine learning models. Python being platform-independent can make this overall training very cheap and easier.

4. Great Community Base

The fact is well that Python’s community has grown across the globe, and especially in the world of machine learning and data science. There are active communities that contribute to the large exchange of information which involves solutions to problems. For any problem you come across, chances are very high that someone out there has already gone through that same problem and solved it successfully. Hence you can find guidance and bits of advice at any level of doubt. You won’t be the only one who went through it. Also, you may come to know some of the best results according to your specifications, all you need to do it to turn to the huge python community.

Ready to learn Python Programming?

Take DataFlair’s self-paced Python training and become the next developer

Summary

Machine learning has made a massive effect on the current world we are living in, with new applications emerging all the time. Developers are choosing Python at every step of problem-solving. While there are programming languages other than python that be used for AI projects, but python is cutting edges of all, with significant considerations. According to the people who practice python, they believe – python is a language that is well suited for machine learning and AI. And if you are still wondering why, read this twice! And choose python for your next AI project.