Modeltime unlocks time series forecast models and machine learning in one framework

A library that unifies the API for most commonly used libraries and modeling techniques for time-series forecasting in the Python ecosystem.

Forecasting building energy demand through time series analysis and machine learning.

Complete solution for MOFC M5 Forecasting in kaggle.

Identified the most appropriate Time-Series method to forecast drought in African countries, acting as a critical early warning for drought managements

Cambridge UK temperature forecast R models

A fable wrapper for TBATS

Panel time-series forecasting notebooks (daily sales across stores × items). Clean validation (holdout + rolling-origin backtest), strong statistical baselines (SARIMAX/TBATS/ARIMA), and automated models (AutoTS), with optional Prophet/Darts/NeuralProphet. Primary metric: SMAPE.

Time series analysis project: forecasting brazilian inflation.

Knowledge of various Time Series Forecasting topics: Long Short-Term Memory (LSTM), Exponential Smoothing, Autoregressive integrated moving average (ARIMA), TBATS, Multivariate Time Series Forecasting, XGboost, N_BEATS, and Prophet.

a short program that analyzes time-series of sales to forecast future demand of certain products from a set of stores

Application of real-time visualization and forecasting of COVID-19 build on R and shiny

Predicting Walmart Sales and Performing Exploratory Data Analysis

Study of time-frequency representations in the presence of heteroscedastic dependent noise

Time series analysis project: forecasting M3 competition series.

STAT497 APPLIED TIME SERIES ANALYSIS term project

This project aims to analyze and forecast daily revenue and the daily number of receipts across six distinct restaurants, by employing a statistical approach and utilizing predictive models, particularly the SARIMA and TBATS models.

Forecasting Fixed Rate Mortgage Average in The United States

A comparative breakdown of traditional econometric timeseries models vs. more modern ML methods for predicting a retail firm's sales over a short to medium horizon

This repository hosts code and models for weather forecasting using TBATS (Trigonometric seasonality, Box-Cox transformation, ARMA errors, Trend, and Seasonal components) models. The project includes data preprocessing, model training, evaluation, and forecasting based on historical daily weather data.