Python As a Preferable For Machine Learning With Mayur Rele

machine language

Machine Learning is a branch of computer science that uses a computer system to analyze data and learn from the experience by predicting the outcome. It can also be called an artificial intelligence that extracts patterns out of raw data using an algorithm. When it comes to Machine Learning language, Python has won the heart of programmers over the years due to its simplicity and consistency.

Benefit of machine learning

As the world develops, newer technologies like Artificial Intelligence are on the high rise. “Although AI hasn’t surpassed human intelligence but with Machine Learning, decisions based on data can be made with efficiency. While we cannot do without human intelligence, we still need to solve bigger problems with efficiency at a huge scale, hence the need for Machine Learning,” says Mayur Rele, a cybersecurity expert.

Machine Learning is needed in various industries like the financial industry where a huge amount of diverse data and records are dealt with. Advanced algorithms are encouraged for share trading, credit approval, and detection of fraud. Also in a medical line, advanced algorithms are used for quick processing, recognizing more patterns, development of drugs, and early detection of disease.

Python benefit for machine learning

Python is a popular programming language that possesses high readability and clarity of source code. It is best for a novice programmer, simple to use, possess multiple applications, secure, and has multiple communities.

It’s no surprise Python is the most used language for Machine Learning. Mayur Rele explains features of python that make it more preferred to other languages for Machine Learning.

  1. Easy and fast prototyping

Python has an easy and fast prototype which makes it useful for developing a new algorithm. This type of feature makes it a choice of Machine Learning.

  1. Great collection of inbuilt libraries 

With its extensive and powerful packages, it has made it easy to use across various domains and industries. Packages like pandas, NumPy, scipy, scikit-learn, and so on are parts of python features.

Implementing a Machine Learning algorithm requires a lot of time and can be tricky, therefore it’s important to have a well-tested and well-structured environment, to help developers with the best coding solutions. With the extensive set of libraries for artificial intelligence, you can develop your product faster using python.

  1. Multipurpose language

Machine learning projects have many domains like data manipulation, data analysis, data extractions, modeling, evaluation, features extraction, deployment, and solution update. With python being one language for many domains, it helps to address the Machine Learning domain from a common platform. The python independence platform has helped a lot of developers to implement it on one machine and use them on another machine with no or minimal changes. Platforms like Linux, Windows, and macOS have been a great support for python. The code can be used to create executable stand-alone programs for a common operating system.

  1. Collaboration

Machine Learning needs good collaboration and python features provide many useful tools for collaboration and usage.

  1. Simplicity and consistency

With its easy learning, python has been the best language programming for new developers. Python codes are readable and concise. Its simplicity allows developers to write reliable systems.

  1. Popularity and great community

As the top ten most popular programming languages, you can hire a development company to build your AI-based project. Python developer survey 2017 observed that python is commonly used for web development. The Python AI community has grown and keeps growing across the globe, hence you can find advice from developers who have dealt with the same problem. Therefore, you can easily approach a python community for best solutions to your needs.