Official community-driven Azure Machine Learning examples, tested with GitHub Actions.
Обновлено 2024-11-09 03:13:44 +03:00
TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data
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DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
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The Website and web infrastructure for learning TypeScript
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ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
Обновлено 2024-11-08 19:55:46 +03:00
Batch Scoring For Deep Learning Models
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ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
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A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Обновлено 2024-11-08 09:19:21 +03:00
HI-ML toolbox for deep learning for medical imaging and Azure integration
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Releasing building footprint polygons for Kenya and Nigeria derived from satellite imagery using machine learning
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VS Code Jupyter extension
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Detect and warn about suspicious IPs logging into Nextcloud
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DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
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Workflow that takes advantage of GATKs CNN tool which is a deep learning approach to filter variants based on Convolutional Neural Networks
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ML.NET is an open source and cross-platform machine learning framework for .NET.
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Resources created by Microsoft's GPS (Global Partner Solutions) team
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Examples for using ONNX Runtime for machine learning inferencing.
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Python notebooks with ML and deep learning examples with Azure Machine Learning Python SDK | Microsoft
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Home of the commercial marketplace learning series.
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Platform for Machine Learning projects on Software Engineering
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DirectML is a high-performance, hardware-accelerated DirectX 12 library for machine learning. DirectML provides GPU acceleration for common machine learning tasks across a broad range of supported hardware and drivers, including all DirectX 12-capable GPUs from vendors such as AMD, Intel, NVIDIA, and Qualcomm.
Обновлено 2024-10-30 20:27:48 +03:00
Azure Machine Learning for Visual Studio Code, previously called Visual Studio Code Tools for AI, is an extension to easily build, train, and deploy machine learning models to the cloud or the edge with Azure Machine Learning service.
Обновлено 2024-10-30 10:28:02 +03:00
Microsoft Finance Time Series Forecasting Framework (FinnTS) is a forecasting package that utilizes cutting-edge time series forecasting and parallelization on the cloud to produce accurate forecasts for financial data.
Обновлено 2024-10-29 17:51:56 +03:00