Time series forecasting with PyTorch
A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
A professional list of Papers, Tutorials, and Surveys on AI for Time Series in top AI conferences and journals.
Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting
A simple and flexible code for Reservoir Computing architectures like Echo State Networks
Modeltime unlocks time series forecast models and machine learning in one framework
Temporal online machines: streaming anomaly detection with calibrated p-values, built on skaters
The fundamental package for AIops with python.
If you can measure it, consider it predicted
Traffic prediction is the task of predicting future traffic measurements (e.g. volume, speed, etc.) in a road network (graph), using historical data (timeseries).
TiRex: Zero-Shot Forecasting Across Long and Short Horizons with Enhanced In-Context Learning
[IJCAI-24] Spatial-Temporal-Decoupled Masked Pre-training for Spatiotemporal Forecasting
Timeseries Anomaly detection and Root Cause Analysis on data in SQL data warehouses and databases
TKAN: Temporal Kolmogorov-Arnold Networks
A python package for time series forecasting with scikit-learn estimators.
A code implementation of new papers in the time series forecasting field.
The official repository of paper "ViTime: A Visual Intelligence-based Foundation Model for Time Series Forecasting"
Template to quickstart streaming analytics using Apache Kafka for ingestion, QuestDB for time-series storage and analytics, Grafana for near real-time dashboards, and Jupyter Notebook for data science
Analyzing the safety (311) dataset published by Azure Open Datasets for Chicago, Boston and New York City using SparkR, SParkSQL, Azure Databricks, visualization using ggplot2 and leaflet. Focus is on descriptive analytics, visualization, clustering, time series forecasting and anomaly detection.