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The Makridakis Competitions (also known as the M Competitions or M-Competitions) are a series of open competitions to evaluate and compare the accuracy of different time series forecasting methods. They are organized by teams led by forecasting researcher Spyros Makridakis and were first held in 1982. [1] [2] [3] [4]
Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC.Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
The Global Energy Forecasting Competition (GEFCom) is a competition conducted by a team led by Dr. Tao Hong that invites submissions around the world for forecasting energy demand. [1] GEFCom was first held in 2012 on Kaggle , [ 2 ] and the second GEFCom was held in 2014 on CrowdANALYTIX.
John Galt Solutions is a privately held software company that provides forecasting and supply chain planning for mid-market companies. [1] [2]Founded in 1996 and headquartered in Chicago, they claim more than 6,000 customers worldwide use John Galt Solutions products every day.
This dataset contains a large collection of Open Neural SPARQL Templates and instances for training Neural SPARQL Machines; it was pre-processed by semi-automatic annotation tools as well as by three SPARQL experts. 894,499 Question-query pairs Question Answering 2018 [332] [333] Hartmann, Soru, and Marx et al.
Forecast either to existing data (static forecast) or "ahead" (dynamic forecast, forward in time) with these ARMA terms. Apply the reverse filter operation (fractional integration to the same level d as in step 1) to the forecasted series, to return the forecast to the original problem units (e.g. turn the ersatz units back into Price).
Simple or fully formed statistical models to describe the likely outcome of the time series in the immediate future, given knowledge of the most recent outcomes (forecasting). Forecasting on time series is usually done using automated statistical software packages and programming languages, such as Julia, Python, R, SAS, SPSS and many others.
Deep learning is a subset of machine learning that focuses on utilizing neural networks to perform tasks such as classification, regression, and representation learning.The field takes inspiration from biological neuroscience and is centered around stacking artificial neurons into layers and "training" them to process data.