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msix-toolkit icon msix-toolkit

MSIX toolkit is a collection of tools for users managing MSIX packages. The toolkit includes tools like appinstaller file generator, ComparePackage visualizer and frequently used PowerShell scripts.

mslab icon mslab

Azure Stack HCI, Windows 10 and Windows Server rapid lab deployment scripts

msmarco-conversational-search icon msmarco-conversational-search

Truly Conversational Search is the next logic step in the journey to generate intelligent and useful AI. To understand what this may mean, researchers have voiced a continuous desire to study how people currently converse with search engines. Traditionally, the desire to produce such a comprehensive dataset has been limited because those who have this data (Search Engines) have a responsibility to their users to maintain their privacy and cannot share the data publicly in a way that upholds the trusts users have in the Search Engines. Given these two powerful forces we believe we have a dataset and paradigm that meets both sets of needs: A artificial public dataset that approximates the true data and an ability to evaluate model performance on the real user behavior. What this means is we released a public dataset which is generated by creating artificial sessions using embedding similarity and will test on the original data. To say this again: we are not releasing any private user data but are releasing what we believe to be a good representation of true user interactions.

msmarco-document-ranking icon msmarco-document-ranking

MS MARCO(Microsoft Machine Reading Comprehension) is a large scale dataset focused on machine reading comprehension, question answering, and passage/document ranking

msmarco-passage-ranking icon msmarco-passage-ranking

MS MARCO(Microsoft Machine Reading Comprehension) is a large scale dataset focused on machine reading comprehension, question answering, and passage ranking. A variant of this task will be the part of TREC and AFIRM 2019. For Updates about TREC 2019 please follow This Repository Passage Reranking task Task Given a query q and a the 1000 most relevant passages P = p1, p2, p3,... p1000, as retrieved by BM25 a succeful system is expected to rerank the most relevant passage as high as possible. For this task not all 1000 relevant items have a human labeled relevant passage. Evaluation will be done using MRR

msmarco-question-answering icon msmarco-question-answering

MS MARCO(Microsoft Machine Reading Comprehension) is a large scale dataset focused on machine reading comprehension and question answering

mso icon mso

Microsoft Open C++ Library

msopentech-tools-for-intellij icon msopentech-tools-for-intellij

Plugin for easy and fast development to enable developers of Android Apps to connect to Office 365 services and Azure Mobile Services, and developers of Java middleware to connect to Azure compute services

msphpsql icon msphpsql

Microsoft Drivers for PHP for SQL Server

msquic icon msquic

Cross-platform, C implementation of the IETF QUIC protocol, exposed to C, C++, C# and Rust.

msr-cloak icon msr-cloak

Code for experiments referenced in the Usenix Security 2017 paper "Strong and Efficient Cache Side-Channel Protection using Hardware Transactional Memory"

msrc-appconfig icon msrc-appconfig

Type safe composable application configuration management in Python

msrd-rest-samples icon msrd-rest-samples

Samples showing how to access Microsoft Security Risk Detection REST API from various languages

msrflute icon msrflute

Federated Learning Utilities and Tools for Experimentation

msrsec icon msrsec

Security and Privacy Research at Microsoft

mssql-django icon mssql-django

The Microsoft Django backend for SQL Server provides a connectivity layer for Django on SQL Server or Azure SQL DB.

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