Search Results for "binary" - Page 2
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Showing 28 open source projects for "binary"
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Polygon Software | Apparel Software | PLM and ERP SolutionsPolyPM is an integrated enterprise resource planning (ERP) and product lifecycle management (PLM) solution developed by Polygon Software. Built for small to medium-sized apparel manufacturers, PolyPM enables businesses to integrate all aspects of the product development, supply chain and production processes, as well as instantly access all their style and manufacturing information anywhere in the world. This allows businesses to shorten time-to-market, incur lower development costs, and improve customer service and worker productivity.
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Business password and access manager solution for IT security teamsEuropean businesses use Uniqkey to simplify password management, reclaim IT control and reduce password-based cyber risk. All in one super easy-to-use tool.
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FEVal, the Finite Element Evaluator written in Python, provides easy conversion for many Finite Element data formats (both binary and ascii). Mesh modification is very easy. Values of model results can be accessed given coordinates in physical space.
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OCFit
Python package for fitting of O-C diagrams.
Python package OCFit includes 4 classes for analysis and fitting of O-C diagrams of Eclipsing binaries In a case of using this package for scientific purposes, please, cite our paper Gajdoš & Parimucha (2018) where you can also find more detail description about fitting functions and used models. For install it, download/clone this repository or download suitable binary file from releases. Not working yet! The first release comming soon... Requirements numpy matplotlib PyAstronomy pymc Installation is possible from source code or using build installation binary file (only for OS Windows). The following procedure is only for installation from the source code. Extract files and go to new-created folder. ... -
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nBoost is a suite of boosting algorithms designed to solve binary classification problems on data that is not linearly separable by a convex combination of base hypotheses, i.e. noisy data. WARNING: Active development. Underlying algorithm is unstable.
