Best Natural Language Processing Software for Spark NLP

BERT is a large language model and a method of pre-training language representations. Pre-training refers to how BERT is first trained on a large source of text, such as Wikipedia. You can then apply the training results to other Natural Language Processing (NLP) tasks, such as question answering and sentiment analysis. With BERT and AI Platform Training, you can train a variety of NLP models in about 30 minutes.

spaCy is designed to help you do real work, build real products, or gather real insights. The library respects your time and tries to avoid wasting it. It's easy to install, and its API is simple and productive. spaCy excels at large-scale information extraction tasks. It's written from the ground up in carefully memory-managed Cython. If your application needs to process entire web dumps, spaCy is the library you want to be using. Since its release in 2015, spaCy has become an industry standard with a huge ecosystem. Choose from a variety of plugins, integrate with your machine learning stack, and build custom components and workflows. Components for named entity recognition, part-of-speech tagging, dependency parsing, sentence segmentation, text classification, lemmatization, morphological analysis, entity linking, and more. Easily extensible with custom components and attributes. Easy model packaging, deployment, and workflow management.