Search Results for "graph class"
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Showing 4 open source projects for "graph class"
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Deliver trusted data with dbtData teams use dbt to codify business logic and make it accessible to the entire organization—for use in reporting, ML modeling, and operational workflows.
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gSOAP Toolkit
Development toolkit for Web Services and XML data bindings for C & C++
The gSOAP toolkit is an extensive suite of portable C and C++ software to develop XML Web services with powerful type-safe XML data bindings. Easy-to-use code-generator tools allow you to directly integrate XML data in C and C++. Serializes native application data in XML. Includes WSDL/XSD schema binding and auto-coding tools, stub/skeleton compiler, Web server integration with Apache module and IIS extension, high-performance XML processing with schema validation, fast MIME/MTOM streaming,... -
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PREESM provides a complete framework for fast prototyping. It generates a simulation and an optimized multiprocessor code from graph descriptions of algorithm and architecture. Please visit the project homepage at http://preesm.sourceforge.net.
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yEdGen
yEdGen can open a flow chart and generate ANSI C code from it.
yEdGen can generate ANSI C code from a graphml file. You can use yEd Graph Editor, save your flow chart (following some yEdGen rules) in graphml and open it with yEdGen to generate ANSI C code. You can extend yEdGen to generate code for other language. This tool is student oriented. -
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GenGMF is a model driven generator framework for the Eclipse GMF graph and map models. It will generate large models from a small template model for you. It is based on Eclipse GMF, AspectJ and openArchitectureWare.
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Cloud data warehouse to power your data-driven innovationBigQuery Studio provides a single, unified interface for all data practitioners of various coding skills to simplify analytics workflows from data ingestion and preparation to data exploration and visualization to ML model creation and use. It also allows you to use simple SQL to access Vertex AI foundational models directly inside BigQuery for text processing tasks, such as sentiment analysis, entity extraction, and many more without having to deal with specialized models.
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