COVID-19 spread shiny dashboard with a forecasting model, countries' trajectories graphs, and cluster analysis tools

Univariate and multivariate time series forecasting, with uncertainty quantification (Python & R)

Time series with torch

Clustering-based Forecasting Method for Individual End-consumer Electricity Consumption Using Smart Grid Data

Forecast uncertainty based on model averaging

Exercises and material of Hyndman & Athanasopoulos's book "Forecasting: Principles and Practice (3rd Ed.)"

Predicting forex rates with high accuracy using MCMC with Bayesian structural time-series

02435 - Decision-Making under Uncertainty

Unsupervised ensemble learning methods for time series forecasting. Bootstrap aggregating (bagging) for double-seasonal time series forecasting and its ensembles.

Using google search trends and machine learning to predict emergency department visits

Incremental median-based ensemble learning method for seasonal time series

Empirical analysis with financial data (MSFT stock returns) in R, with the goal to produce useful forecasts using univariate, multivariate time series models and volatility models.

Time Series Forecasting using K-Nearest Neighbors Algorithm (Parallel approach)

Density-based clustering unsupervised ensemble learning methods for forecasting double seasonal time series

with Kaggle data

R package consisting of functions and tools to facilitate the use of traditional time series and machine learning models to generate forecasts on univariate or multvariate data. Different backtesting scenarios are available to identify the best performing models.

📚 Time Series Analysis and Forecasting in R

Data for M5 Walmart Kaggle Competition

Neural networks (and other highly questionable approaches) for time series forecasting via fable

Electric Load Curve analysis of ERCOT data