manashgoswami

manashgoswami

Geek Repo

Company:microsoft

Location:San Francisco Bay Area

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manashgoswami's repositories

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azure-docs

Open source documentation of Microsoft Azure

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azure-intelligent-edge-patterns

Samples for Intelligent Edge Patterns

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azure-iot-samples-csharp

azure-iot-samples-csharp provides a set of easy-to-understand, continuously-tested samples for using Azure IoT Hub and Azure IoT Hub Device Provisioning Service using C# SDK.

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azureml-flight-delay

Azure Machine Learning demo on flight delay prediction (work in progress)

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azureml-workshop-2019

AzureML Workshop for the 2019 Euro Tour

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Custom-vision-service-iot-edge-raspberry-pi

Sample showing how to deploy a AI model from the Custom Vision service to a Raspberry Pi 3 device using Azure IoT Edge

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Intelligent-Video-Analytics-with-NVIDIA-Jetson-and-Microsoft-Azure

A repository demonstrating an end-to-end architecture for Intelligent Video Analytics using NVIDIA hardware with Microsoft Azure

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IntelVisionIoTSample

Sample that show hardware acceleration using onnx and other methods from Azure

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IoTEdgeAndMlSample

A sample showing how to take advantage of the intelligent edge using Azure ML, IoT and Edge

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keras-yolo3

A Keras implementation of YOLOv3 (Tensorflow backend)

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MachineLearningNotebooks

Python notebooks with ML and deep learning examples with Azure Machine Learning | Microsoft

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models

The ONNX Model Zoo is a collection of pre-trained, state-of-the-art models in the ONNX format

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nvidia-bert

Use onnxruntime backend on fork of NVIDIA/DeepLearningExamples/PyTorch/LanguageModeling/BERT

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onnx-odsc-tutorial

Tutorial for training PyTorch and Scikit-Learn machine learning models, converting them to onnx format, inferencing the converted model with onnxruntime and finally deploying them to Azure.

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onnx-tensorrt

ONNX-TensorRT: TensorRT backend for ONNX

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onnxruntime

ONNX Runtime: cross-platform, high performance scoring engine for ML models

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onnxruntime-iot-edge

reference implementation to use ONNX Runtime with Azure IoT Edge

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tutorials

Tutorials for creating and using ONNX models

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