time-series

Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).

This curated list contains python packages for time series analysis

A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.

A Python toolkit/library for reality-centric machine/deep learning & data mining on partially-observed time series, with 50+ SOTA neural network models for scientific analysis tasks (imputation, classification, clustering, forecasting, anomaly detection, cleaning) on incomplete industrial irregularly-sampled multivariate TS with NaN missing values

[ICLR 2024] Official implementation of "TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting"

A Python package for time series classification

Code Repository for Liquid Time-Constant Networks (LTCs)

[PVLDB 2024 Best Paper Nomination] TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods

Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics.

Synthetic data generators for tabular and time-series data

Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Unified Training of Universal Time Series Forecasting Transformers

ArcadeDB Multi-Model Database, one DBMS that supports SQL, Cypher, Gremlin, HTTP/JSON, MongoDB and Redis. ArcadeDB is a conceptual fork of OrientDB, the first Multi-Model DBMS. ArcadeDB supports Vector Embeddings.

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

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.

Flexible time series feature extraction & processing

This is the official repository for the book Transformers - The Definitive Guide

A curated collection of AI, data engineering, and DevOps projects featuring real-world applications, advanced techniques, and tutorials—ideal for learners and practitioners exploring data science and machine learning.

PyTorch code for ETSformer: Exponential Smoothing Transformers for Time-series Forecasting

PyTorch implementation of Transformer model used in "Deep Transformer Models for Time Series Forecasting: The Influenza Prevalence Case"