Best Languages For Machine Learning in 2023

Best Languages For Machine Learning in 2023

“A baby learns to crawl, walk and then run.  We are in the crawling stage when it comes to applying machine learning.”

Are you a Amazon customer? Have you ever wondered how world’s largest e-commerce company makes personalized suggestions on what should you buy?

It is possible with the help of artificial intelligence and machine learning.  As per the company, nearly 36% of its sales comes from such personalized recommendations ! Nearly 55% of them are likely to turn into repeat buyers as well. 

Machine learning and artificial intelligence are the stars here! 

Machine Learning
Machine Learning

What is Machine Learning and How it works?

According to Wikipedia:

Machine learning (ML) is a field of inquiry devoted to understanding and building methods that ‘learn’, that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of Artificial Intelligence.

In other words, it is something, where the computer “learns” about something without being explicitly programmed. Machine learning analyses data, interprets it, learns from it, and makes the best possible decisions based on a set of learning algorithms.

Machine Learning is a technology for the future. This blog will focus on the  top programming languages that will stay in demand in 2023 for Machine Learning. 

1. Python

Python is a popular object-oriented programing language having the capabilities of high-level programming language. So it can do a set of complex machine learning tasks and enable you to build prototypes quickly and test your product. Python is easy to use and learn because it’s flexible and has fewer possibilities for error.

2. Java

Java is used for larger projects in machine learning because it has high speed of execution. Java offers many Libraries for implementing Machine Learning. Java’s frameworks provide complete access to calculations, scientific capabilities, and more.

3. R Language

R is a top open-source data visualization-driven language. R was developed by statisticians so it is suitable for better understanding of the underlying details and build innovative. R is an ideal language for exploratory work in statistical models at the beginning of a project.

4. C++

C++ is suitable for machine learning  because of its faster run-time.  C++ supports re-use of programs, so you can save time and cost. Google uses C++ in Artificial Intelligence and Machine Learning programs for SEO (Search Engine Optimization).

So, Which ML Language should you choose?

Programming knowledge is important to learn machine learning. It gives an idea on how you want to use machine learning.  There is no best language for machine learning, each is good where it fits best. Machine learning engineers choose a machine learning language based on the kind of problem they’re working on.