Subseasonal forecasting models
Обновлено 2024-11-07 02:35:52 +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
Samples, templates and setup guides in order to run demand forecasting in Azure Machine Learning Service and integrate with Dynamics 365 SCM
Обновлено 2024-09-26 16:34:31 +03:00
Spectral Temporal Graph Neural Network (StemGNN in short) for Multivariate Time-series Forecasting
Обновлено 2023-07-07 01:23:08 +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
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-powered custom visual. Based on exponential smoothing time series forecasting
Обновлено 2023-06-02 23:39:02 +03:00
Repo to showcase solution examples and learning content curated by the advanced analytics experts within Microsoft Finance
Обновлено 2022-09-02 22:38:04 +03:00
Forecasting models, development, evaluation, and validation
Обновлено 2022-01-11 21:12:40 +03:00
FOST is a general forecasting tool, which demonstrate our experience and advanced technology in practical forecasting domains, including temporal, spatial-temporal and hierarchical forecasting. Current general forecasting tools (Gluon-TS by amazon, Prophet by facebook etc.) can not process and model structural graph data, especially in spatial domains, also those tools suffer from tradeoff between usability and accuracy. To address these challenges, we design and develop FOST and aims to empower engineers and data scientists to build high-accuracy and easy-usability forecasting tools.
Обновлено 2022-01-06 09:18:00 +03:00
Analyzing the safety (311) dataset published by Azure Open Datasets for Chicago, Boston and New York City using SparkR, SParkSQL, Azure Databricks, visualization using ggplot2 and leaflet. Focus is on descriptive analytics, visualization, clustering, time series forecasting and anomaly detection.
Обновлено 2021-05-03 23:14:01 +03:00
A tutorial demonstrating how to implement deep learning models for time series forecasting
Обновлено 2020-11-13 21:01:26 +03:00
For (Potential) Use in Forecasting FxA SMS Spend
Обновлено 2018-10-15 11:40:05 +03:00
This repo contains all the materials and instructions for putting together a Oil & Gas Tank Level Forecasting solution for oil and gas companies using the Cortana Intelligence Suite.
Обновлено 2018-10-01 15:09:55 +03:00
Energy industry solutions using the Cortana Intelligence Suite with end-to-end walkthrough.
Обновлено 2018-09-27 19:48:49 +03:00
Adjoint to Oil Tank Forecasting SHTG
Обновлено 2017-07-21 16:49:44 +03:00
Cortana Intelligence Solution for Shipping and Distribution Forecasting
Обновлено 2017-07-11 20:49:14 +03:00
Cortana Intelligence solution Oil and Gas Tank Level Forecasting
Обновлено 2017-02-04 05:26:40 +03:00
The code to accompany “Time-series-forecasting-using-CNTK” tutorial on Cortana Intelligence Gallery .
Обновлено 2016-11-29 00:51:32 +03:00