#Forecasting
Showing 60 of 109 repositories tagged #forecasting, ranked by stars
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
Statsmodels: statistical modeling and econometrics in Python
Fast and Accurate ML in 3 Lines of Code
A unified framework for machine learning with time series
A python library for user-friendly forecasting and anomaly detection on time series.
Curated list of Machine Learning, NLP, Vision, Recommender Systems Project Ideas
Postgres with GPUs for ML/AI apps.
The GitHub repository for the paper "Informer" accepted by AAAI 2021.
Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai
Chronos: Pretrained Models for Time Series Forecasting
Probabilistic time series modeling in Python
Time series forecasting with PyTorch
Lightning ⚡️ fast forecasting with statistical and econometric models.
Merlion: A Machine Learning Framework for Time Series Intelligence
NeuralProphet: A simple forecasting package
Scalable and user friendly neural :brain: forecasting algorithms.
TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.
A professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.
[AAAI-23 Oral] Official implementation of the paper "Are Transformers Effective for Time Series Forecasting?"
Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
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
A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.
A professional list of Papers, Tutorials, and Surveys on AI for Time Series in top AI conferences and journals.
Unified Training of Universal Time Series Forecasting Transformers
Stock Price Prediction using Machine Learning Techniques
Python library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models
Automated Time Series Forecasting
A toolkit for time series machine learning and deep learning
Django Ledger is a double entry accounting system and financial analysis engine built on the Django Web Framework.
Scalable machine 🤖 learning for time series forecasting.
Non-Intrusive Load Monitoring Toolkit (nilmtk)
tfts: Time Series Deep Learning Models in TensorFlow
ETNA – Time-Series Library
Resources about time series forecasting and deep learning.
Compilation of high-profile real-world examples of failed machine learning projects
Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.
Time series analysis in the `tidyverse`
Modeltime unlocks time series forecast models and machine learning in one framework
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.
Code release for "Non-stationary Transformers: Exploring the Stationarity in Time Series Forecasting" (NeurIPS 2022), https://arxiv.org/abs/2205.14415
Temporal Causal Discovery Framework (PyTorch): discovering causal relationships between time series
PyAF is an Open Source Python library for Automatic Time Series Forecasting built on top of popular pydata modules.
Tools for time series analysis and forecasting
Open-source Bayesian trading AI agent for prediction markets.
The practitioner's forecasting library
Traffic prediction is the task of predicting future traffic measurements (e.g. volume, speed, etc.) in a road network (graph), using historical data (timeseries).
Time Series Analysis with Python Cookbook, published by Packt
An open source library for Fuzzy Time Series in Python
Timeseries for everyone
The Predictive Ecosystem Analyzer (PEcAn) is an integrated ecological bioinformatics toolbox.
Extensive and accessible COVID-19 data + forecasting for counties and hospitals. 📈
scores: Metrics for the verification, evaluation and optimisation of forecasts, predictions or models.
Easy to Deploy Prediction Market Platform
Data Science algorithms for Qlik implemented as a Python Server Side Extension (SSE).
Scripts and notebooks to accompany the book Data-Driven Methods for Dynamic Systems
Applied Time Series Analysis and Forecasting
A professional list of Papers, Tutorials, and Surveys on AI for Time Series in top AI conferences and journals.
Datasets for Predictive Maintenance