What programming languages are suitable for Natural Language Processing?
Probably you already know that natural languages, which are used by humans for communications, are difficult to define with a specific set of rules. By using the combined power of computer science, computational linguistics, and artificial intelligence, NLP or natural language processing helps machines to understand that natural language. The technique uses machine-based algorithms that have the ability to obtain meaning from communication both verbal and written. Natural language processing is widely used in language translation, recognizing human speech, information retrieval etc.
While some may argue that programming language is just a tool to equip an NLP project, it all boils down to which language you’re most comfortable with, which language comes with the maximum number of tools that would help you in performing NLP-related tasks etc. If you’re planning to step into the field of natural language processing and are wondering which programming language you should learn to propel your move, here’re the ones you should focus on.
Python is considered the Swiss Army Knife of programming because of its versatility. It’s also one of the most beginner-friendly languages with its language that mirrors humans and consistent syntax. Python also comes with lots of packages using which code reusability can be done. Its semantics and syntax are transparent which make it a great choice for natural language processing. In addition, it’s simple and provides amazing support for integration with other tools and languages. However, probably the biggest advantage of using Python for natural language processing is that it offers developers a lot of libraries which handle many NLP-related tasks like topic modeling, document classification, sentiment analysis etc. It’s undoubtedly difficult to develop software which can handle natural language. But Python’s extensive toolkit empowers developers to build excellent tools.
Java is another commonly used programming language in the field of natural language processing. With the help of this language, you can explore how to organize text utilizing full-text search, information extraction, clustering, and tagging. As Java is a platform-independent language, it makes the processing of information easy. It comes with OpenNLP, LingPipe, and Stanford CoreNLP. In addition, Lucene, which is a full-text search library, can also help in providing tokenization and comprehensive text analysis.
While R is popular for being used in statistical learning, it’s widely used for natural language processing. In the context of NLP, the language plays a crucial role when it comes to investigating big data and also becomes helpful for computationally intense learning analytics.
While some other languages are also being used for natural language processing, the above ones belong to the most popular group. But it’s always advisable to start with Python when you’re just starting out your journey toward natural language processing field. There’re lots of things that make Python the best programming language for a natural language processing project. Probably the most notable characteristic of this language is its natural language processing libraries like NLTK (Natural Language Toolkit), TextBlob, Gensim, spaCY, polyglot etc that have helped a lot of developers in delivering quality NLP projects.
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To learn more about natural language processing, click here and read our another article.
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