Conformal Time Series Forecasting Using State of Art Machine Learning Algorithms

flexible time series forecasting using machine learning

Placed third 🥉— forecasts groundwater levels in Austria for a 2-year period using data from 487 measurement stations, thousands of CSV files, and 11 variables categorized under four headings: groundwater, precipitation, water source, and surface water, achieving a 0.15 SMAPE score.

Dynamic estimation of taxi rides and time series analysis