Navigating the Future: The Go-to Natural Language Processing APIs of 2023
Exploring the Best NLP APIs for Your Business Needs in 2023 and Beyond
Top Natural Language Processing APIs to Use in 2023
Natural language processing (NLP) is becoming ubiquitous, with new applications popping out constantly. Companies and individuals alike are reaping the advantages of text processing and text analysis APIs. So, which ones should you consider? We’ve rounded up some of the most promising NLP APIs for 2023 and beyond.
GPT-3
To start, we have to mention GPT-3, a go-to API for language model enthusiasts. It’s renowned for text generation capabilities that empower creating content with remarkable coherence. The ability to pre-train on 175 billion parameters gives it an edge in accuracy.
Google NLP API
Google Cloud NLP API is rich with pre-trained models for various tasks: entity extraction, content categorisation, and sentiment analysis. It leverages ML and AI to understand context and derive insights from supplied documents.
Azure
Microsoft Azure is a tool that excels in language identification, entity recognition, sentiment analysis and key phrase extraction. Its inbuilt tutorials help in swift implementation.
Apache OpenNLP
If you prefer open-source tools, consider Apache OpenNLP. Praised for accessibility, it offers practical solutions for sentence detection, tokenisation, POS tagging, and named entity recognition.
NLTK
For Python developers, NLTK offers a suite of text-processing libraries for tokenisation, tagging, parsing, categorisation, and more. Its library of corpora and lexical resources is impressive, and the active community always extends help in mastering it.
SpaCy
SpaCy stands out for tokenisation, among its many capabilities. With word vectors and pre-trained statistical models, it’s a formidable tool for most real-world NLP projects.
Stanford CoreNLP
Java-based Stanford CoreNLP is admired for its vast capabilities. It offers syntactic and semantic parsing, co-reference resolution and sentiment analysis, among other things. Its scalability makes it fit for complex tasks.
Text Blob
Text Blob, developed by NLTK, is lauded as one of the quickest NLP tools. It offers a variety of features and proves an asset in text translation and sentiment analysis.
AllenNLP
AllenNLP shines in text preprocessing and prototyping. While it might not be as optimised as SpaCy for production, it is excellent for research and backed by PyTorch, it allows a great deal of model flexibility.
PyTorch
PyTorch, Facebook’s open-source library, is great for content-based filtering and categorisation. Its integration with Python makes it a popular choice among developers.
BERT
Lastly, Google’s BERT is a bi-directional transformer that excels in understanding the context of a word in relation to other words in a sentence. Its multi-language support makes it more versatile.
These are just some of the APIs that are making strides now, but there are always new and exciting developments happening in the world of NLP. For a more extensive and detailed analysis of these APIs, head on over to https://fastdatascience.com/top-nlp-apis.
