Kalshi's markets aggregate information from diverse traders with financial incentives, creating a "wisdom of the crowd" ...
Abstract: Long-term forecasting for time series is gaining significant attention in many emerging fields, such as machine learning and artificial intelligence. Linear fuzzy information granulation is ...
Objectives To project the future burden of cancer mortality in India by forecasting age-standardised mortality rates (ASMRs) for 23 major cancer types up to the year 2030, providing crucial evidence ...
A range of national meteorological services across Europe and ECMWF have launched Anemoi, a framework for creating machine learning (ML) weather forecasting systems. Named after the Greek gods of the ...
In forecasting economic time series, statistical models often need to be complemented with a process to impose various constraints in a smooth manner. Systematically imposing constraints and retaining ...
Temperature impacts every part of the world. Meteorological analysis and weather forecasting play a crucial role in sustainable development by helping reduce the damage caused by extreme weather ...
The analysis uses a comprehensive household energy dataset with: ...
This repository contains a 7-lesson FREE course to teach you how to build a production-ready ML batch system. Its primary focus is to engineer a scalable system using MLOps good practices. You will ...
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