10 Powerful Programming Languages For Doing Machine Learning
In computer science, Machine learning and artificial intelligence are the fastest-growing areas. Those who are working with these technologies are in the win. In recent times, more and more industries and businesses are inheriting machine learning and artificial intelligence. ML and AI are providing a world of endless opportunities. Almost every other business is using machine learning services in any way.
According to the recent report, there has been a 34% growth in AI/machine learning patents. Apple, Google, Microsoft, and many other tech giants are pouring money in AI and ML. International Data Corporation (IDC) forecasts that spending on AI and ML will grow from $12 billion in 2017 to $57.6 billion by 2021.(source)
Programming Languages For Machine Learning
There are thousands of programming languages. But you need not study all of them. Before learning ML it is important to know which language is best for ML. Here we will discuss the top programming languages for machine learning.
1. Python
Python is the best machine learning language to learn for beginners. Syntax of Python is so easy. Apart from machine learning services, it can be used for various purposes. It is a high level, open-source, general-purpose programming language. It supports imperative, functional, object-oriented, and procedural development paradigms as it is a dynamic language.
2. Scala
Scala is a popular name in big data. Scala runs way faster than Python as it uses Java virtual machine at runtime.It has a library called “Aerosolve” for machine learning which is especially designed for human beings. Apache Spark includes tools like Microsoft machine learning.
These tools are designed to use with distributed computing framework.
3. C++
C++ is one of the most widely accepted popular and oldest programming languages. Including Tensorflow, most of the machine learning platform supports C++. C++ is an object-oriented, general-purpose programming language. There are a lot of machine learning libraries in C++ like mlpack and Shark. Both are open-source libraries used to highlight ease of use, speed and scalability.
4. Golang
Golang is a widely used machine learning language developed by Google. It is a safe, open-source, statically typed, general-purpose programming language. Syntax of Go is similar to C. It has a lot of rich standard libraries like GoLearn, Gorgonia, Goml. Go is a compiled programming languages like C and C++. Go is easy to learn a language because of its syntax.
5. R
R programming language build environment for graphics and statical computing. R programming language offers a wide range of graphical and statical techniques like classical statistical tests, linear and nonlinear modelling, classification, time-series analysis, clustering, etc. R offers some packages for machine learning like Caret, MLR, and H2O.
6. Java
Java is the widely used programming language in all over the world. It s also an open-source general-purpose programming language. The first implementation of Java as Java 1.0 was developed by Sun Microsystems. Later it was acquired by Oracle. Some Java libraries used for machine learning services are JDMP, MLlib(spark) and WEKA.
7. Julia
Julia first appeared in the market in the year 2012. It is a high performance, dynamic programming language. Julia combines features from other programming languages like speed from Java and C++ and other functionalities from R, Python, and Stata languages. Machine learning libraries that Julia have are ScikitLearn.jl, MLBase.jl, and MachineLearning.jl.
8. C#
C# is a simple, easy, flexible, modern, safe, open-source, and object-oriented programming language. C# is one of the most versatile programming languages in the world. C# allows application developers to build all kind of applications including consoles, mobile apps, Web apps, Windows clients, and backend systems. C# in machine learning can be used with the help of .NET.
9. JavaScript
JavaScript is an object-oriented programming language. JavaScript was one of the technologies behind the World Wide Web apart from HTML and CSS. It is also used at the front end development of several famous websites like Google, Facebook, YouTube, Wikipedia, and Amazon. It is also used in popular web frameworks like Node.js, AngularJS, and React.JS.
10. Haskell
Haskell is a robust static typing language. Haskell offers support for embedded domain-specific languages, which is crucial for AI research. It uses common algebraic structures, such as monoids and modules for enhancing the efficiency of Machine Learning algorithms. Haskell is much popular in academics circle however many reputed organizations use Haskell in their projects.
Conclusion
Language is the most relevant form of APIs used by global AI and machine learning developers as of 2019, as 55.9% of surveyed AI and machine learning developers said that their organizations relied on language APIs. (source)
Learning a machine learning programming language can benefit you in various ways. Nowadays there is a huge demand for machine learning software providers and hire machine learning developers in the market.
#Machine-Learning #Python #Scala #Golang #Java
