Top 5 Natural Language Processing Tools For 2021 - NLP Development in Australia

Top 5 Natural Language Processing (NLP) Tools For 2021

What is NLP?

Natural language processing (NLP) is a subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language, how to program computers to process and analyze large amounts of natural language data.

Common NLP tasks

  • Text and speech processing
  • Morphological analysis
  • Syntactic analysis
  • Lexical semantics
  • Relational semantics
  • Discourse

Markets and Markets says, the global Natural Language Processing (NLP) market size to grow from USD  11.6 billion in 2020 to USD 35.1 billion by 2026, at a Compound Annual Growth Rate (CAGR) of 20.3% during the forecast period.

Top 5 Natural Language Processing Tools For 2021

  • An open-source machine learning framework that accelerates the path from research prototyping to production deployment.
  • PyTorch enables fast, flexible experimentation and efficient production through a user-friendly front-end, distributed training, and ecosystem of tools and libraries.
  • It is well supported on major cloud platforms, providing frictionless development and easy scaling.

  • spaCy is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython.
  • It excels at large-scale information extraction tasks and is designed to help build real products or gather real insights.
  • The library respects your time and tries to avoid wasting it. It is easy to install, and its API is simple and productive.

  • Gensim is an open-source library for unsupervised topic modeling and natural language processing, using modern statistical machine learning.
  • It is implemented in Python and Cython for performance and is designed to handle large text collections using data streaming and incremental online algorithms.
  • The open-source code is developed and hosted on GitHub and a public support forum is maintained on Google Groups and Gitter.

  • Bidirectional Encoder Representations from Transformers (BERT) is a transformer-based machine learning technique for natural language processing (NLP) pre-training developed by Google.
  • It has two models: the BERTBASE and the BERTLARGE.
  • It makes use of a transformer, an attention mechanism that learns contextual relations between words (or sub-words) in a text.

  • The Natural Language Toolkit, or more commonly NLTK, is a suite of libraries and programs for symbolic and statistical natural language processing (NLP) for English written in the Python programming language.
  • It is intended to support research and teaching in NLP or closely related areas, including empirical linguistics, cognitive science, artificial intelligence, information retrieval, and machine learning.
  • It supports classification, tokenization, stemming, tagging, parsing, and semantic reasoning functionalities.

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