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.
microsoft
machine-learning
deep-learning
data-science
r
finance
time-series
forecasting
business
finnts
r-package
rstats
Обновлено 2024-08-05 18:19:32 +03:00
R package for analyzing and visualizing data from Microsoft Workplace Analytics
Обновлено 2024-07-26 19:03:52 +03:00
Utility functions for easier usage of SQL Server Machine Learning Services
Обновлено 2024-07-12 23:52:03 +03:00
Density-based spatial clustering of applications with noise visualization
Обновлено 2024-04-16 11:25:20 +03:00
Samples, templates and setup guides in order to run demand forecasting in Azure Machine Learning Service and integrate with Dynamics 365 SCM
Обновлено 2024-03-18 17:35:39 +03:00
R SDK for interacting with Microsoft 365 APIs
r
azure-sdk-r
microsoft-graph-api
office-365
onedrive
microsoft-365
onedrive-for-business
sharepoint-online
Обновлено 2024-02-23 16:58:15 +03:00
Anomaly detection analysis and labeling tool, specifically for multiple time series (one time series per category)
Обновлено 2024-02-08 18:29:01 +03:00
R interface to Azure Data Explorer, aka Kusto
Обновлено 2023-10-13 17:29:01 +03:00
R package for interacting with Azure Resource Manager
Обновлено 2023-09-20 02:59:06 +03:00
R interface to Microsoft Graph REST API
Обновлено 2023-09-06 10:23:39 +03:00
Zoom Data Integration with Viva Insights
Обновлено 2023-08-16 17:35:08 +03:00
Find outliers in your data, using a funnel plot
Обновлено 2023-07-08 06:35:09 +03:00
This repo contains a walkthrough of how to use RServer for HDInsight with large data sets like Criteo.
Обновлено 2023-06-27 16:07:15 +03:00
This is a sample R ShinyApp application which shows how to query data from a SQL Azure database in the Microsoft Azure cloud and visualise that data, which contains geospacial coordinates, onto a World Map.
Обновлено 2023-06-27 16:05:21 +03:00
Develop Portable R Code for Use with DeployR
Обновлено 2023-06-14 18:19:32 +03:00
R-powered custom visual implementing the “Seasonal and Trend decomposition using Loess” algorithm, offering several types of plots. Time series decomposition is an essential analytics tool to understand the time series components and to improve forecasting.
Обновлено 2023-06-12 23:28:34 +03:00
This solution template shows how to build and deploy a loan-credit-risk solution with Microsoft ML Server
Обновлено 2023-06-12 23:03:52 +03:00
This solution template demonstrates how to build and deploy a retail online fraud detection solution.
Обновлено 2023-06-12 23:02:25 +03:00
Loan ChargeOff Risk Solution Template with Microsoft ML Server
Обновлено 2023-06-12 23:02:02 +03:00
An R-powered custom visual implementing Autoregressive Integrated Moving Average (ARIMA) modeling for the forecasting. Time series forecasting is the use of a model to predict future values based on previously observed values.
Обновлено 2023-06-12 21:29:06 +03:00
R library for common information retrieval metrics
Обновлено 2023-06-05 13:06:42 +03:00
R-powered custom visual. Based on exponential smoothing time series forecasting
Обновлено 2023-06-02 23:39:02 +03:00
R-powered custom visual. Implements k-means clustering
Обновлено 2023-06-02 23:39:02 +03:00
Find outliers in your data, using the most appropriate method and plot.
Обновлено 2023-06-02 22:13:49 +03:00
Обновлено 2023-03-28 19:48:16 +03:00
R package for working with containers in Azure: ACI, ACR, AKS
kubernetes
r
containers
azure-container-registry
azure-kubernetes-service
azure-sdk-r
azure-container-instances
Обновлено 2023-03-28 19:44:41 +03:00
R interface to Azure Key Vault
Обновлено 2023-03-28 19:44:40 +03:00
R interface to VM instance metadata
Обновлено 2023-03-28 19:44:30 +03:00
R package for managing virtual machines in Azure
Обновлено 2023-01-30 08:49:07 +03:00