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Several mainstream AI programming languages
Several mainstream AI programming languages
01 Python
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Python syntax is simple and functional. It is one of developers' favorite AI development programming languages. For developers, the application of Python in machine learning is very gratifying, because it is simpler than C + + and Java languages. Python is also a very portable language, because it can be used on Linux, Windows, Mac OS and UNIX platform. Python is also very popular with developers, because it allows developers to create interactive, interpretable, modular, dynamic, portable, and advanced code, which makes it more unique than the Java language.
In addition, Python is a multi paradigm programming language, supporting object-oriented, process oriented and functional programming styles. Because it has simple function library and ideal structure, Python is very suitable for the development of neural network and Natural Language Processing (NLP) solution.
advantage
Python has a rich variety of libraries and tools.
In the case of no need to implement the algorithm test.
Python's object-oriented design improves the efficiency of developers.
Compared with Java and C + +, Python run faster in development.
shortcoming
Developers who are accustomed to using Python try to use other languages to do AI programming, so it is hard to adjust them to different syntax.
Unlike the C + + and Java, Python run in an interpreter's help, in the development of AI which will make the compilation and execution becomes slower.
It is not suitable for mobile computing.
02 C++
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Advantage
C + + is the fastest computer language, it is especially suitable for time sensitive AI programming project. C + + provides faster execution time and response time (which is why it is often used to search engine and game). In addition, C + + algorithm allows the use of large scale, and in the use of statistical AI technology is very efficient. Another important factor is the inheritance and data hiding, in the development of C + + supports the reuse of code, so to save time and money.
C + + is suitable for machine learning and neural network.
shortcoming
Multi tasking effect; C + + is only applicable to the core or basic implementation of a specific system or algorithm.
C++ follows the bottom-up approach, so it is very complicated.
03 Java
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Java is also a multi paradigm language. It follows the principles of object-oriented and the principles of WORA programming. Java is a AI programming language running on any platform supporting it without recompilation.
In addition to the AI development, Java is one of the most commonly used language, the most compatible syntax of C and C + + in. Java is applied not only to Natural Language Processing and search algorithm, but also to neural network.
04 LISP
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Advantage:
Lisp is the second oldest programming language after family relay Fortran. Over time, LISP has developed into a powerful and dynamic programming language.
Some people think that Lisp is the best AI programming language, because it provides freedom for developers. The use of Lisp in AI development is due to its flexibility in making rapid modeling and experiments possible, which in turn promotes the development of Lisp in AI development. For example, Lisp has a unique macro system that can help explore and achieve different levels of intelligence.
Unlike most AI programming languages, Lisp is more efficient in solving specific problems, because it can meet the needs of developers to write solutions. Lisp is very suitable for inductive logic projects and machine learning.
Shortcomings:
Few developers are familiar with Lisp programming.
As an old programming language, Lisp needs to configure new software and hardware to adapt to the current environment.
05 Prolog
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Prolog is also one of the oldest programming languages, so it is also suitable for the development of AI. Like Lisp, it is also the main AI programming language. The mechanism of Prolog can develop a more flexible framework welcomed by developers. Prolog is a rule based and declarative language, because it has the facts and rules of AI programming language.
Prolog supports basic mechanisms, such as pattern matching, tree based data structure, and automatic backtracking required by AI programming. Besides being widely used in AI projects, Prolog is also applied to create medical systems.
640? Wx_fmt=jpeg&wxfrom=5&wx_lazy=1
Python syntax is simple and functional. It is one of developers' favorite AI development programming languages. For developers, the application of Python in machine learning is very gratifying, because it is simpler than C + + and Java languages. Python is also a very portable language, because it can be used on Linux, Windows, Mac OS and UNIX platform. Python is also very popular with developers, because it allows developers to create interactive, interpretable, modular, dynamic, portable, and advanced code, which makes it more unique than the Java language.
In addition, Python is a multi paradigm programming language, supporting object-oriented, process oriented and functional programming styles. Because it has simple function library and ideal structure, Python is very suitable for the development of neural network and Natural Language Processing (NLP) solution.
advantage
Python has a rich variety of libraries and tools.
In the case of no need to implement the algorithm test.
Python's object-oriented design improves the efficiency of developers.
Compared with Java and C + +, Python run faster in development.
shortcoming
Developers who are accustomed to using Python try to use other languages to do AI programming, so it is hard to adjust them to different syntax.
Unlike the C + + and Java, Python run in an interpreter's help, in the development of AI which will make the compilation and execution becomes slower.
It is not suitable for mobile computing.
02 C++
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Advantage
C + + is the fastest computer language, it is especially suitable for time sensitive AI programming project. C + + provides faster execution time and response time (which is why it is often used to search engine and game). In addition, C + + algorithm allows the use of large scale, and in the use of statistical AI technology is very efficient. Another important factor is the inheritance and data hiding, in the development of C + + supports the reuse of code, so to save time and money.
C + + is suitable for machine learning and neural network.
shortcoming
Multi tasking effect; C + + is only applicable to the core or basic implementation of a specific system or algorithm.
C++ follows the bottom-up approach, so it is very complicated.
03 Java
640? Wx_fmt=jpeg
Java is also a multi paradigm language. It follows the principles of object-oriented and the principles of WORA programming. Java is a AI programming language running on any platform supporting it without recompilation.
In addition to the AI development, Java is one of the most commonly used language, the most compatible syntax of C and C + + in. Java is applied not only to Natural Language Processing and search algorithm, but also to neural network.
04 LISP
640? Wx_fmt=jpeg
Advantage:
Lisp is the second oldest programming language after family relay Fortran. Over time, LISP has developed into a powerful and dynamic programming language.
Some people think that Lisp is the best AI programming language, because it provides freedom for developers. The use of Lisp in AI development is due to its flexibility in making rapid modeling and experiments possible, which in turn promotes the development of Lisp in AI development. For example, Lisp has a unique macro system that can help explore and achieve different levels of intelligence.
Unlike most AI programming languages, Lisp is more efficient in solving specific problems, because it can meet the needs of developers to write solutions. Lisp is very suitable for inductive logic projects and machine learning.
Shortcomings:
Few developers are familiar with Lisp programming.
As an old programming language, Lisp needs to configure new software and hardware to adapt to the current environment.
05 Prolog
640? Wx_fmt=png
Prolog is also one of the oldest programming languages, so it is also suitable for the development of AI. Like Lisp, it is also the main AI programming language. The mechanism of Prolog can develop a more flexible framework welcomed by developers. Prolog is a rule based and declarative language, because it has the facts and rules of AI programming language.
Prolog supports basic mechanisms, such as pattern matching, tree based data structure, and automatic backtracking required by AI programming. Besides being widely used in AI projects, Prolog is also applied to create medical systems.