What Are The Top 5 Machine Learning Languages You Should Learn – The Complete List
In modern times, machine learning languages are the most demanded profession in multiple industry domains. Along with Bayas theorem machine learning was introduced theoretically in the year 1763. In order to make the machines intelligent, you can apply various machine learning techniques. Alan Turing discovered the first machine learning in early 1950.
Purpose of Machine learning:
In the field of computer science, machine learning is a subset of artificial intelligence. Machine learning is made with an intention so that the computers can easily adapt the learning ability by not being programmed. Machine language makes the computer learn to analyze and interpret the data. This is the why our phones have become smart.
Top 5 machine learning languages that you should master:
Python:
Python programming language was first released in the year 1991 by Guido Van Rossum. It is a scripting language like PHP, Perl, Ruby, etc. You can use Python programming language for Web programming. At Intel, testing microchips become easier with it. Other than this, you can also use Python for powering Instagram or constructing video games. Because of simplicity and easy to learn, it has become the most popular language. Machine learning uses the linear algebra and kernel method. Python contains specific libraries like numpy and scipy that helps to use these methods.
R Programming:
R is a popular language for statistical computing and graphics. Statisticians and data miners widely use R for various purposes. R is the most suitable software which you can use for creating projects such as report making or research papers. It is an open source root to research in analytical methodology. Being a powerful programming language, it offers effective data handling and storage facility. Another key point is that by defining new functions it allows users to add additional functionality.
LISP:
LISP, also known as list processor language is the primary language that is employed for AI work in the United States. It is the second oldest programming language used today. Besides this, LISP also works as a practical mathematical notation for the computer. Compilers can use LISP because it works with a medium of powerful and fast coding. For example Grammarly, which is a cloud-based program, where you can write documents, make messages, interact with the writings and make it mistake free.
Prolog:
Like LISP, Another old language created for programming Artificial Intelligence is Prolog. Being a declarative language, Prolog uses a method in which it first defines and then it solves the logical formulas. In addition to this, Prolog provides expert ways that can be implemented in a system, pattern matching and mechanism to handle list. You can suitably use Prolog application in the quantitative training field and natural language processing projects
Javascript:
Java is a popular client-side scripting language. Characterized by dynamic, weakly-typed, prototype-based and multi-paradigm, Javascript is the most popular programming language. Javascript has a unique graphical representation of data that helps in better users interaction. With the compelled features, it has always been the good choice for AI development. Java contributes a lot in network security or cyber-attacks and fraud detection projects. It also supports event-driven, functional and imperative programming styles.
Winding it up
Above all, the importance of machine learning languages cannot be denied. Depending upon users requirements and predilections, the machine language chooses a programming language. Experience the machine learning techniques with unique features and usage of programming language.
