Introducing IBM Watson NLP Library for Embed, a containerized library designed to empower IBM partners with greater flexibility to infuse powerful natural language AI into their solutions. It combines the best of open source and IBM® Research® NLP algorithms to deliver superior AI capabilities developers can access and integrate into their apps in the environment of their choice. Offered to partners as embeddable AI, a first of its kind software portfolio that offers best of breed AI from IBM.
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IBM Watson NLP Library for Embed offers algorithmic choice and modular design so you can integrate NLP capabilities in your solution with greater flexibility to meet your specific needs.
Deploy and run your applications on any hybrid multi cloud in the container environment of your choice: local Docker platform, Kubernetes, or serverless containers.
Analyze sentiment on a positive, negative, and neutral scale to determine whether a customer is happy or dissatisfied, pinpoint the reason why, and find specific moments where sentiment changed.
Detects anger, disgust, fear, joy or sadness that is conveyed in the content or by the context around target phrases specified in the targets parameter.
Analyze and classify desired text using custom label classifier trained in Watson Studio.
Detect, extract, prepare, redact personally identifiable information (PII), or classify mentions of entities from raw text data.
Extract all mentions of keywords, phrases and expressions a from text input.
Extract semantic relationships from text which usually occur between two or more entities.
Extract concepts of interest that are referenced or alluded to and groups words and phrases into semantically similar groups.
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IBM Watson NLP Library for Embed, powered by Intel processors and optimized with Intel software tools, uses deep learning techniques to extract meaning and meta data from unstructured data.
Integrating Intel’s OneAPI and IBM Watson’s NLP Library can accelerate the performance of various NLP tasks, including sentiment analysis, topic modeling, named entity recognition, keyword extraction, text classification, entity categorization, and word embeddings.
A quick overview of the integration of IBM Watson NLU and accelerators on Intel Xeon-based infrastructure with links to various resources.
CrushBank empowers IT help desk employees to quickly find the most relevant information to solve customers’ problems, increasing productivity and customer satisfaction.
LegalMation uses natural language processing to help legal teams draft high-quality litigation work in minutes, freeing time and resources for higher-tier services.
The Watson Natural Language Processing (NLP) Library for Embed provides natural language processing functions for syntax analysis, and pre-trained models for a wide variety of text processing tasks, in a fully embeddable library.
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