Showing 8 open source projects for "numerical python files"

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  • 1
    DAE Tools Project

    DAE Tools Project

    Object-oriented equation-based modelling and optimisation software

    DAE Tools is a cross-platform equation-based object-oriented modelling, simulation and optimisation software. It is not a modelling language nor a collection of numerical libraries but rather a higher level structure – an architectural design of interdependent software components providing an API for: - Model development/specification - Activities on developed models, such as simulation, optimisation, sensitivity analysis and parameter estimation - Processing of the results, such as...
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    Downloads: 14 This Week
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  • 2
    smclarify

    smclarify

    Fairness aware machine learning. Bias detection and mitigation

    Fairness Aware Machine Learning. Bias detection and mitigation for datasets and models. A facet is column or feature that will be used to measure bias against. A facet can have value(s) that designates that sample as "sensitive". Bias detection and mitigation for datasets and models. The label is a column or feature which is the target for training a machine learning model. The label can have value(s) that designates that sample as having a "positive" outcome. A bias measure is a function...
    Downloads: 0 This Week
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  • 3
    DeepCTR-Torch

    DeepCTR-Torch

    Easy-to-use,Modular and Extendible package of deep-learning models

    DeepCTR-Torch is an easy-to-use, Modular and Extendible package of deep-learning-based CTR models along with lots of core components layers that can be used to build your own custom model easily.It is compatible with PyTorch.You can use any complex model with model.fit() and model.predict(). With the great success of deep learning, DNN-based techniques have been widely used in CTR estimation tasks. The data in the CTR estimation task usually includes high sparse,high cardinality categorical...
    Downloads: 2 This Week
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  • 4
    SageMaker Chainer Containers

    SageMaker Chainer Containers

    Docker container for running Chainer scripts to train and host Chainer

    ...Amazon SageMaker utilizes Docker containers to run all training jobs & inference endpoints. The Docker images are built from the Dockerfiles specified in Docker/. The Docker files are grouped based on Chainer version and separated based on Python version and processor type. The Docker images, used to run training & inference jobs, are built from both corresponding "base" and "final" Dockerfiles. The "base" Dockerfile encompasses the installation of the framework and all of the dependencies needed. All "final" Dockerfiles build images using base images that use the tagging scheme.
    Downloads: 1 This Week
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  • 5
    Jmr - Java Code Generator

    Jmr - Java Code Generator

    "black technology" will improve development productivity by 1.5 to 5

    More than just an entirely free Java code generator, It's also a development automation tool(Much more than a normal code generator). Maybe it can become your "black technology" will improve development productivity by 1.5 to 5 times, Zero coupling to your project and without changing anything. Normal code generator flow: Template → Source Code Jmr development automation flow: Template/Model/Action → Task → Source Code/Test Case/Document Template: Support Java...
    Downloads: 1 This Week
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  • 6
    Image classification models for Keras

    Image classification models for Keras

    Keras code and weights files for popular deep learning models

    All architectures are compatible with both TensorFlow and Theano, and upon instantiation the models will be built according to the image dimension ordering set in your Keras configuration file at ~/.keras/keras.json. For instance, if you have set image_dim_ordering=tf, then any model loaded from this repository will get built according to the TensorFlow dimension ordering convention, "Width-Height-Depth". Pre-trained weights can be automatically loaded upon instantiation (weights='imagenet'...
    Downloads: 0 This Week
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  • 7
    PETRILab

    PETRILab

    Simulador de Redes de Petri Interpretadas para Controle

    O PETRILab é um software multiplataforma desenvolvido inteiramente em Python. Ele permite a modelagem e simulação de Redes de Petri Interpretadas para Controle (RPIC), tendo suporte a todos seus elementos: lugares, transições, arcos ordinários e inibidores, eventos, condições e ações. Com uma interface gráfica simples e intuitiva, o usuário consegue modelar e simular passo-a-passo sua RPIC de forma rápida e prática, afim de estudá-la e aprimorá-la.
    Downloads: 2 This Week
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  • 8
    An AToM3 definition of a CASE framework for creating Zope products with files in the filesystem. The framework consists of a modelling notation ZProduct and a suit of related transformations.
    Downloads: 0 This Week
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