🎁 Shows recommended files in Nextcloud
Обновлено 2024-09-17 11:50:06 +03:00
Best Practices on Recommendation Systems
azure
microsoft
machine-learning
python
deep-learning
kubernetes
data-science
artificial-intelligence
jupyter-notebook
tutorial
operationalization
ranking
rating
recommendation
recommendation-algorithm
recommendation-engine
recommendation-system
recommender
Обновлено 2024-09-17 05:40:34 +03:00
Azure monitor workbook from FTA vTeam focusing on reliability recommendations for deployed resources on Azure
Обновлено 2024-09-04 01:10:36 +03:00
Telemetry-Aware Addon Recommender
Обновлено 2023-07-25 18:14:05 +03:00
Product Recommendations solution
Обновлено 2023-07-09 10:59:33 +03:00
Sample code to integrate Microsoft Cognitive Services Recommendations API in Microsoft Dynamics AX 2012R3 Call Center module
Обновлено 2023-03-28 19:47:03 +03:00
Sample Project for creating an RRS Recommendation System using AzureML
Обновлено 2023-03-28 19:45:47 +03:00
Azure Service Manager (Classic) migration to Azure Resource Manager, options, recommendations and guidelines.
Обновлено 2022-11-28 22:34:57 +03:00
Art Recommendations with the Microsoft HoloLens
Обновлено 2022-11-28 22:10:32 +03:00
A fast numpy-based implementation of ranking metrics for information retrieval and recommendation.
Обновлено 2022-08-22 22:05:09 +03:00
This is a solution accelerator for creating personalized content recommendations based on user activity.
Обновлено 2022-03-17 22:45:10 +03:00
Implementation of "Debiasing Item-to-Item Recommendations With Small Annotated Datasets" (RecSys '20)
Обновлено 2020-10-13 21:31:30 +03:00
Peregrine is a workload optimization platform for cloud query engines. The goal of Peregrine is three-fold: 1. make it easier to ingest and analyze query workload telemetry into a common engine-agnostic representation, 2. help developers to quickly build workload optimization applications to reduce overall costs and improve operational efficiency, and 3. providing better experience to the customers in the form of workload insights, actionable recommendations, and self-tuning capabilities.
Обновлено 2020-08-31 07:53:14 +03:00
An example cross-platform movie recommendation application built using Xamarin.Forms and Azure ML service
Обновлено 2019-10-04 21:36:40 +03:00
Stand-alone verison of Add-on Recommendation for Shield Study
Обновлено 2019-04-02 00:04:56 +03:00
Recommendation server for Universal Search.
Обновлено 2016-11-30 20:00:05 +03:00
Completed Test Pilot experiment: add-on that inserts server recommendations into the Awesome Bar
Обновлено 2016-11-30 19:48:03 +03:00
INACTIVE - http://mzl.la/ghe-archive - Short-term hack for contextual recommendation of links
Обновлено 2016-07-15 09:20:48 +03:00
New Tab page: content server and recommendation service
Обновлено 2015-10-01 10:45:57 +03:00
DEPRECATED - Recommendations Serving Engine using python
Обновлено 2015-08-28 23:33:25 +03:00