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🎁Extracts entities, keywords, categories, emotions, and syntax from text using advanced NLP.
Built for compliance, scalability, and secure deployment across hybrid cloud environments.
Offers ready-to-use AI services for language, vision, and automation tasks.
Provides transparency into model decisions with bias detection and interpretability tools.
Sign up for IBM Cloud and access Watson services via dashboard or CLI.
Select from NLP, Assistant, Discovery, or Speech-to-Text APIs based on your use case.
Use Python, Node.js, or REST APIs to connect Watson to your application.
Feed data into Watson and fine-tune models or use pre-trained endpoints.
Deploy models securely and monitor performance with built-in dashboards.
from ibm_watson import NaturalLanguageUnderstandingV1
from ibm_watson.natural_language_understanding_v1 import Features, EntitiesOptions, KeywordsOptions
from ibm_cloud_sdk_core.authenticators import IAMAuthenticator
# Authenticate
authenticator = IAMAuthenticator('your-api-key')
nlu = NaturalLanguageUnderstandingV1(
version='2021-08-01',
authenticator=authenticator
)
nlu.set_service_url('https://api.us-south.natural-language-understanding.watson.cloud.ibm.com')
# Analyze text
response = nlu.analyze(
text='IBM Watson is a powerful AI platform.',
features=Features(entities=EntitiesOptions(), keywords=KeywordsOptions())
).get_result()
print(response)
Build AI assistants that understand queries and respond with contextual accuracy.
Extract insights from contracts, reports, and PDFs using NLP and classification.
Used for clinical decision support, patient engagement, and medical literature analysis.
Detects sentiment, trends, and anomalies in financial documents and news feeds.
Explore IBM Watson’s ecosystem and find the tools, platforms, and docs to accelerate your workflow.
Common questions about IBM Watson’s capabilities, usage, and ecosystem.