ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
Обновлено 2024-11-08 15:58:39 +03:00
Official community-driven Azure Machine Learning examples, tested with GitHub Actions.
Обновлено 2024-11-07 21:03:38 +03:00
💻📦 The Nextcloud VM (virtual machine appliance), Home/SME Server and scripts for RPi (4). Community developed and maintained.
Обновлено 2024-11-07 20:27:41 +03:00
Smart camera tools for passionate creators
Обновлено 2024-11-07 19:18:50 +03:00
Training pipelines for Firefox Translations neural machine translation models
Обновлено 2024-11-07 07:45:55 +03:00
VS Code Jupyter extension
Обновлено 2024-11-07 07:39:04 +03:00
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Обновлено 2024-11-07 07:38:21 +03:00
Visual Studio Code Remote Development: Open any folder in WSL, in a Docker container, or on a remote machine using SSH and take advantage of VS Code's full feature set.
Обновлено 2024-11-07 04:32:57 +03:00
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 2024-11-07 01:00:08 +03:00
Detect and warn about suspicious IPs logging into Nextcloud
Обновлено 2024-11-06 21:30:41 +03:00
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.
Обновлено 2024-11-06 18:53:00 +03:00
A modular services stack that facilitates remote Linux devices management over Azure
Обновлено 2024-11-06 00:02:12 +03:00
ML.NET is an open source and cross-platform machine learning framework for .NET.
Обновлено 2024-11-05 20:27:05 +03:00
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 2024-11-05 15:04:38 +03:00
HI-ML toolbox for deep learning for medical imaging and Azure integration
Обновлено 2024-11-05 02:07:14 +03:00
Examples for using ONNX Runtime for machine learning inferencing.
Обновлено 2024-11-05 01:51:35 +03:00
Linux Virtual Machine Extensions for Azure
Обновлено 2024-11-04 20:47:17 +03:00
This machine kills superstition. 💨
Обновлено 2024-11-04 20:38:43 +03:00
Python notebooks with ML and deep learning examples with Azure Machine Learning Python SDK | Microsoft
Обновлено 2024-11-04 20:20:56 +03:00
Platform for Machine Learning projects on Software Engineering
Обновлено 2024-11-04 06:54:44 +03:00
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 Guest Configuration Virtual Machine Extension for Linux
Обновлено 2024-10-30 19:49:34 +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
The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
Обновлено 2024-10-28 14:18:34 +03:00
This package features data-science related tasks for developing new recognizers for Presidio. It is used for the evaluation of the entire system, as well as for evaluating specific PII recognizers or PII detection models.
Обновлено 2024-10-27 15:51:02 +03:00