Showing 5 open source projects for "neural net python"

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  • 1
    Synapse Machine Learning

    Synapse Machine Learning

    Simple and distributed Machine Learning

    SynapseML (previously MMLSpark) is an open source library to simplify the creation of scalable machine learning pipelines. SynapseML builds on Apache Spark and SparkML to enable new kinds of machine learning, analytics, and model deployment workflows. SynapseML adds many deep learning and data science tools to the Spark ecosystem, including seamless integration of Spark Machine Learning pipelines with the Open Neural Network Exchange (ONNX), LightGBM, The Cognitive Services, Vowpal Wabbit,...
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  • 2
    TensorFlow.NET

    TensorFlow.NET

    .NET Standard bindings for Google's TensorFlow for developing models

    ...SciSharp STACK's mission is to bring popular data science technology into the .NET world and to provide .NET developers with a powerful Machine Learning tool set without reinventing the wheel. Since the APIs are kept as similar as possible you can immediately adapt any existing TensorFlow code in C# or F# with a zero learning curve. Take a look at a comparison picture and see how comfortably a TensorFlow/Python script translates into a C# program with TensorFlow.NET.
    Downloads: 1 This Week
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  • 3
    Forecasting Best Practices

    Forecasting Best Practices

    Time Series Forecasting Best Practices & Examples

    Time series forecasting is one of the most important topics in data science. Almost every business needs to predict the future in order to make better decisions and allocate resources more effectively. This repository provides examples and best practice guidelines for building forecasting solutions. The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in forecasting algorithms to build solutions and operationalize them. Rather than...
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  • 4
    Deep Learning with PyTorch

    Deep Learning with PyTorch

    Latest techniques in deep learning and representation learning

    This course concerns the latest techniques in deep learning and representation learning, focusing on supervised and unsupervised deep learning, embedding methods, metric learning, convolutional and recurrent nets, with applications to computer vision, natural language understanding, and speech recognition. The prerequisites include DS-GA 1001 Intro to Data Science or a graduate-level machine learning course. To be able to follow the exercises, you are going to need a laptop with Miniconda (a...
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    DSTK - Data Science TooKit 3

    DSTK - Data Science TooKit 3

    Data and Text Mining Software for Everyone

    DSTK - Data Science Toolkit 3 is a set of data and text mining softwares, following the CRISP DM model. DSTK offers data understanding using statistical and text analysis, data preparation using normalization and text processing, modeling and evaluation for machine learning and algorithms. It is based on the old version DSTK at https://sourceforge.net/projects/dstk2/ DSTK Engine is like R. DSTK ScriptWriter offers GUI to write DSTK script. DSTK Studio offers SPSS Statistics like GUI...
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