Natural Language Processing, aka NLP, is a cross discipline that is at the intersection of linguistics, machine learning and artificial intelligence and that is experimenting a great popularity recently because it lies at the heart of many widely used applications, like automatic translators and summarizers, virtual assistants, search autocorrection and autocompletion, chatbots, targeted advertising, social media monitoring, data extraction from texts and much more.
If you are someone involved in this field, either as an engineer or as a CEO or as a decision maker it is hence obvious asking which programming language is the best text processing language, so as to be sure it is adopted in your NLP project.
And the winner is…Python!
Python is one of the most popular programming languages, thanks to its simplicity and versatility. Many artificial intelligence programs and apps are written in Python and there are many libraries (e.g. NumPy, Pandas, Pybrain, SciPy, Spacy, PyTorch, Keras…) that are ready to use for machine learning, statistics and maths. It has a strong supportive community and it is not linked to any particular platform or operating system. It has also powerful visualization packages, which is something good when you have to make things understandable.
Second best: Java
Java is a widely diffused, object-oriented language that enjoys a wealth of libraries (like Weka or Deeplearning4j) and is completely platform independent thanks to its virtual machine technology. It is perfectly at ease with big data projects and is used also by big players like Amazon. It is quite user friendly and it allows graphical representation of data. It is also considered a secure language, so it is surely a wise choice and can surely be considered one of the best text processing language.
Developed by MIT as a tool to handle numerical computing problems (for which it has an extensive library), it is now available on an open source basis and though it is still a niche language is gaining popularity, thanks to the ease with which it can translate ideas from research papers into operating code. It offers a dynamic type system and is able to work for parallel and distributed computing programs. It has a syntax similar to that of Python and performances as good as those of C. It aims at unifying the best aspects of the best text processing languages, like Python, Java and C++.
R it is a graphics based language aimed at analyzing statistical data via visual representations. It is widely used in machine learning because with it it’s easy to handle tasks such as regression, classification, and so on. R is mostly suited for scientific fields like bioengineering, astronomy, genomics and – thanks to its data modeling potential – machine learning and text processing. It is quite hard to learn for newbies and people without a background in statistics.