Search Results for "shader model 2.0)"
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Showing 12 open source projects for "shader model 2.0)"
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ProcureDesk is an integrated purchasing and invoicing platform tailored to help small to medium sized businesses streamline their procurement processes. This user-friendly system automates workflows and consolidates purchasing data into a centralized dashboard, allowing companies to control spending and enhance transparency efficiently. Features like automated invoice matching, simple requisition creation, and immediate cash flow insights minimize manual tasks and boost operational efficiency. ProcureDesk is perfect for smaller enterprises leveraging big-business strategies to reduce costs and optimize their purchasing activities. Discover how ProcureDesk can transform your procurement process into a more effective and manageable part of your business.
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BigQuery 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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TOMUSS
TOMUSS: The Online Multi User Simple Spreadsheet
TOMUSS is an interactive web application (groupware) allowing multiple concurrent users to edit data tables. Its primary goal is the management of students grades. -
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The Deep Review
A collaboratively written review paper on deep learning, genomics, etc
This repository is home to the Deep Review, a review article on deep learning in precision medicine. The Deep Review is collaboratively written on GitHub using a tool called Manubot (see below). The project operates on an open contribution model, welcoming contributions from anyone. To see what's incoming, check the open pull requests. For project discussion and planning see the Issues. As of writing, we are aiming to publish an update of the deep review. We will continue to make project... -
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PyMathProg
An easy and flexible mathematical programming environment for Python.
PyMathProg is a Python reincarnation of AMPL and GNU MathProg modeling language, implemented in pure Python, connecting to GLPK via swiglpk. Create, optimize, report, change and re-optimize your model with Python, easily integrate database, plotting, etc. -
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The General Hidden Markov Model Library (GHMM) is a C library with additional Python bindings implementing a wide range of types of Hidden Markov Models and algorithms: discrete, continous emissions, basic training, HMM clustering, HMM mixtures.
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We design our technology to make workforce management easier. APS offers core HR, payroll, benefits administration, attendance, recruiting, employee onboarding, and more.
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BibteXML is a bibliography schema for XML that expresses the content model of BibTeX – the bibliographic system for use with LaTeX. Stylesheets and conversion tools are provided.
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The Campaign Simulator is an attempt to statistically model and predict the outcome of an American presidential election; several users assume the roles of competitive candidates and inflict the repercussions of certain decisions on a GSS based dataset.
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Yabman is a tool for managing bibliographic references. Its key features are a quality user interface, a carefully designed data model, and sophisticated three-state hierarchical reference labeling. It is currently usable but in a pre-alpha stage.
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This is a implementation of the 'enhanced Topic-based Vector Space Model' (eTVSM) using the python language. A Java-Version and maybe other java-code contributions are planned.
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MoPs is an interactive intelligent tutoring system that helps children learning to read and spell German words. It uses a special didactic model (known as the "Häusermodell") and has the full approval of the creators of this model.
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Calmerry is beneficial for businesses of all sizes, particularly those in high-stress industries, organizations with remote teams, and HR departments seeking to improve employee well-being and productivity
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This is an educational example of how to run a numerical model (in Fortran) from Python, including data handling (netCDF), configuration with a config file, etc.
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Implementation of Generalized Linear Model (GLM) for regression in python. Christopher M. Bishop uses this as an example for various concepts in "Pattern Recognition and Machine Learning".
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This is a scholar project to make an implementation of the enterprise real-life model built by the mexican government.
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