Machine Learning Languages

LISP is the second oldest programming language in the world (1958), one year younger than Fortran (1957).

The term Artificial Intelligence was made up by John McCarthy who invented LISP.

LISP was founded on the theory of Recursive Functions (self modifying functions), and this is very suitable for Machine Learning programs where "self-learning" is an important part of the program.

The R Language R is a programming language for Graphics and Statistical computing. R is supported by the R Foundation for Statistical Computing . R comes with a wide set of statistical and graphical techniques for: Linear Modeling Nonlinear Modeling Statistical Tests Time-series Analysis Classification Clustering Python Python is a general-purpose coding language. It can be used for all types of programming and software development. Python is typically used for server development, like building web apps for web servers. Python is also typically used in Data Science . An advantage for using Python is that it comes with some very suitable libraries: NumPy (Library for working with Arrays) SciPy (Library for Statistical Science) Matplotlib (Graph Plotting Library) NLTK (Natural Language Toolkit) TensorFlow (Machine Learning) Source: Octoverse C++ C++ holds the title: " The worlds fastest programming language ". Because of the speed, C++ is a preferred language when programming Computer Games. It provides faster execution and has less response time which is applied in search engines and development of computer games. Google uses C++ in Artificial Intelligence and Machine Learning programs for SEO (Search Engine Optimization). SHARK is a super-fast C++ library with support for supervised learning algorithms, linear regression, neural networks, and clustering. MLPACK is also a super-fast machine learning library for C++. Java Java is another general-purpose coding language that can be used for all types of software development. For Machine Learning, Java is mostly used to create algorithms, and neural networks. SQL SQL (Structured Query Language) is the most popular language for managing data. Knowledge of SQL databases, tables and queries helps data scientists when dealing with data. SQL is very convenient for storing, manipulating, and retrieving data in databases.

R is a programming language for Graphics and Statistical computing.

R is supported by the R Foundation for Statistical Computing .

R comes with a wide set of statistical and graphical techniques for:

• Linear Modeling
• Nonlinear Modeling
• Statistical Tests
• Time-series Analysis
• Classification
• Clustering

Python is a general-purpose coding language. It can be used for all types of programming and software development.

Python is typically used for server development, like building web apps for web servers.

Python is also typically used in Data Science .

An advantage for using Python is that it comes with some very suitable libraries:

• NumPy (Library for working with Arrays)
• SciPy (Library for Statistical Science)
• Matplotlib (Graph Plotting Library)
• NLTK (Natural Language Toolkit)
• TensorFlow (Machine Learning)

Source: Octoverse

C++ holds the title: " The worlds fastest programming language ".

Because of the speed, C++ is a preferred language when programming Computer Games.

It provides faster execution and has less response time which is applied in search engines and development of computer games. Google uses C++ in Artificial Intelligence and Machine Learning programs for SEO (Search Engine Optimization). SHARK is a super-fast C++ library with support for supervised learning algorithms, linear regression, neural networks, and clustering. MLPACK is also a super-fast machine learning library for C++. Java Java is another general-purpose coding language that can be used for all types of software development. For Machine Learning, Java is mostly used to create algorithms, and neural networks. SQL SQL (Structured Query Language) is the most popular language for managing data. Knowledge of SQL databases, tables and queries helps data scientists when dealing with data. SQL is very convenient for storing, manipulating, and retrieving data in databases.

Google uses C++ in Artificial Intelligence and Machine Learning programs for SEO (Search Engine Optimization).

SHARK is a super-fast C++ library with support for supervised learning algorithms, linear regression, neural networks, and clustering.

MLPACK is also a super-fast machine learning library for C++.

Java is another general-purpose coding language that can be used for all types of software development.

For Machine Learning, Java is mostly used to create algorithms, and neural networks.

SQL (Structured Query Language) is the most popular language for managing data.

Knowledge of SQL databases, tables and queries helps data scientists when dealing with data.

SQL is very convenient for storing, manipulating, and retrieving data in databases.