Everything you need to build production-ready agents and models. Access 200+ Google and third-party AI models and tools.
Gemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
Try It Free
Custom VMs From 1 to 96 vCPUs With 99.95% Uptime
General-purpose, compute-optimized, or GPU/TPU-accelerated. Built to your exact specs.
Live migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
JTextPro: A Java-based Text Processing tool that includes sentence boundary detection (using maximum entropy classifier), word tokenization (following Penn conventions), part-of-speech tagging (using CRFTagger), and phrase chunking (using CRFChunker).
CRFTagger: Conditional Random Fields Part-of-Speech (POS) Tagger for English. The model was trained on sections 01..24 of WSJ corpus and using section 00 as the development test set (accuracy of 97.00%). Tagging speed: 500 sentences/s.
Lay a foundation for success with Tested Reference Architectures developed by Fortinet’s experts. Learn more in this white paper.
Moving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
AutoSummary uses Natural Language Processing to generate a contextually-relevant synopsis of plain text. It uses statistical and rule-based methods for part-of-speech tagging, word sense disambiguation, sentence deconstruction and semantic analysis.
jATLAS is a Java implementation of ATLAS [Architecture and Tools for Linguistic Analysis Systems]. For more information, see http://jatlas.sourceforge.net.
This is a project to create a compiler that converts grammars written in SRGS standard (http://www.w3.org/TR/speech-grammar/) to a graph understandable by HMM based ASR engines. Check srgs-parser.sf.net