Statsmodels: statistical modeling and econometrics in Python

A professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.

Apache HoraeDB (incubating) is a high-performance, distributed, cloud native time-series database.

A professional list of Papers, Tutorials, and Surveys on AI for Time Series in top AI conferences and journals.

GRASS - free and open-source geospatial processing engine

Official code for TimeCraft: A Time Series Generation Framework for Real-World Applications

Time series easier, faster, more fun. Pytimetk.

A Python library for detecting patterns and anomalies in massive datasets using the Matrix Profile

A simple and flexible code for Reservoir Computing architectures like Echo State Networks

Real-time anomaly detection for time series metrics. 11 years of production anomaly detection evolution. Multi-algorithm ensembles. Pattern recognition using semi-supervised and unsupervised learning. Correlation analysis. Learns and gets better over time. No GPU required, can run on a VPS.

[VLDB' 25] ChatTS: LLM for Time Series Understanding and Reasoning

Temporal online machines: streaming anomaly detection with calibrated p-values, built on skaters

If you can measure it, consider it predicted

Python implementation of k-Shape

API for manipulating time series on top of Apache Spark: lagged time values, rolling statistics (mean, avg, sum, count, etc), AS OF joins, downsampling, and interpolation

ML based projects such as Spam Classification, Time Series Analysis, Text Classification using Random Forest, Deep Learning, Bayesian, Xgboost in Python

trend / momentum and other patterns in financial timeseries

Time-Series Anomaly Detection Comprehensive Benchmark

Public Fused UDFs. Build any scale workflows with the Fused Python SDK and Workbench webapp, and integrate them into your stack with the Fused Hosted API.

This tool should help discover different patterns based on similarity measures in historical (financial) data