Why to use Python for Machine Learning and AI?

AI (Artificial Intelligence) and ML (Machine Learning) based projects are certainly what the future holds. In today’s world, we want smarter recommendations, improved search functionality and enhanced personalization. The current apps can respond to our queries- that’s what AI and ML has brought, creating value across several industries and enhancing user experience.

With the increase in complexity of data, ML and AI are used for processing and analyzing it. Although human brain can analyze large data, its ability to absorb data at any moment is limited – And, AI is absolutely free from this limitation.

Why use Python for AI and ML?

Python programming language offers stability, flexibility and has various tools available, which is why we see a lot of companies using Python in their AI projects today.

From development to maintenance of the project, Python helps software developers be productive about the product they are building. Reasons that make Python the ideal fit for ML and AI-based projects are: consistency and simplicity, access to vast libraries, flexibility, wide community network and platform independence.

Consistent and simple

Python provides readable and concise code. While sophisticated algorithms stand behind AI and machine learning, Python’s simple code enables developers to write reliable software codes. Instead of spending more time on the nuances of the language, developers can put all their effort and time into solving logical and ML problems.

Python is relatively very easy to learn, which attracts many developers to learn the language. Since Python code is easily understandable by humans, it makes it simpler to develop models.

Access to libraries and frameworks

It is very important to have a well-designed and well-structured programming language to help developers to deliver the best coding solutions as implementing ML and AI algorithms consumes a lot of time and can be tricky at times.

To reduce development time, developers look for a number of libraries and frameworks. With its rich technology stack, Python has a broad spectrum of libraries for AL and ML and a few of them are:

– TensorFlow, Keras, and Scikit-learn for ML

– SciPy for advanced computing

– NumPy for data analysis and scientific computing

– Pandas for data analysis

Platform independent

One of the key factors to Python’s fame is that it is platform independent, which means it allows developers to implement things on one system and use it on another system with minimal or no changes. Python is supported by different platforms like Windows, macOS, and Linux.

Excellent Community

Python programming language was among the top 10 most famous languages in 2018, which means that you will spot a development company with all the needed skill set to build your next AI-based project.

Bottom line

The reason why most developers consider Python as the perfect programming language for AI and ML is because: Python is amazingly flexible, it has low entry barrier, it offers extensive library system, it is easy to read, and many more

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