forecasting

Scalable machine 🤖 learning for time series forecasting.

A professional list on Large (Language) Models and Foundation Models (LLM, LM, FM) for Time Series, Spatiotemporal, and Event Data.

Time-series machine learning at scale. Built with Polars for embarrassingly parallel feature extraction and forecasts on panel data.

Forecasting Functions for Time Series and Linear Models

Non-Intrusive Load Monitoring Toolkit (nilmtk)

tfts: Time Series Deep Learning Models in TensorFlow

MOMENT: A Family of Open Time-series Foundation Models, ICML'24

Luminaire is a python package that provides ML driven solutions for monitoring time series data.

Resources about time series forecasting and deep learning.

Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.

Compilation of high-profile real-world examples of failed machine learning projects

PyTorch Dual-Attention LSTM-Autoencoder For Multivariate Time Series

A unified multi-task time series model.

Time series analysis in the `tidyverse`

TimeCopilot: the GenAI Forecasting Agent. Built on LLMs and Time Series Foundation Models, it lets you forecast, cross-validate, and detect anomalies using multiple foundation models through a single API. From finance and energy to web analytics, TimeCopilot turns natural-language queries into production-ready forecasts.

Tidy time series forecasting

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

Code release for "Non-stationary Transformers: Exploring the Stationarity in Time Series Forecasting" (NeurIPS 2022), https://arxiv.org/abs/2205.14415