#Time-series-forecasting
Showing 60 of 68 repositories tagged #time-series-forecasting, ranked by stars
Chronos: Pretrained Models for Time Series Forecasting
Probabilistic time series modeling in Python
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 🚀.
This repository contains a reading list of papers on Time Series Forecasting/Prediction (TSF) and Spatio-Temporal Forecasting/Prediction (STF). These papers are mainly categorized according to the type of model.
A professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.
List of papers, code and experiments using deep learning for time series forecasting
[ICLR 2024] Official implementation of " 🦙 Time-LLM: Time Series Forecasting by Reprogramming Large Language Models"
Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BER
[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).
AssetOpsBench - Industry 4.0: A unified benchmark and framework for building, orchestrating, and evaluating domain-specific AI agents for Industry 4.0 asset operations and maintenance, with 460+ scenarios, 4 specialist agents (IoT, FMSR, TSFM, Work Order), and multi-agent orchestration blueprints (MetaAgent, AgentHive) over MCP.
[ICLR 2024] Official implementation of "TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting"
[PVLDB 2024 Best Paper Nomination] TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods
Unified Training of Universal Time Series Forecasting Transformers
Python library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models
Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)
[ICLR 2025 Spotlight] Official implementation of "Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts"
Time-Series Work Summary in CS Top Conferences (NIPS, ICML, ICLR, KDD, AAAI, WWW, IJCAI, CIKM, ICDM, ICDE, etc.)
time series analysis tutorial
tfts: Time Series Deep Learning Models in TensorFlow
Resources about time series forecasting and deep learning.
Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.
Resources for working with time series and sequence data
Python Client and Toolkit for DataFrames, Big Data, Machine Learning and ETL in Elasticsearch
A use-case focused tutorial for time series forecasting with python
Official implementation of our ICLR 2023 paper "Crossformer: Transformer Utilizing Cross-Dimension Dependency for Multivariate Time Series Forecasting"
Forecasting electric power load of Delhi using ARIMA, RNN, LSTM, and GRU models
DEPRECATED, now in sktime - companion package for deep learning based on TensorFlow
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.
Unofficial implementation of iTransformer - SOTA Time Series Forecasting using Attention networks, out of Tsinghua / Ant group
Acquiring data from Alpha Vantage and predicting stock prices with PyTorch's LSTM
Traffic prediction is the task of predicting future traffic measurements (e.g. volume, speed, etc.) in a road network (graph), using historical data (timeseries).
Awesome time series forecasting papers and codes
Book and material for the course "Time series analysis with Python" (STA-2003)
An open source library for Fuzzy Time Series in Python
time series analysis models source code
Time Series Analysis and Forecasting in Python
An open cloud native capacity solution which helps you achieve ultimate resource utilization in an intelligent and risk-free way.
Pull stock prices from online API and perform predictions using Long Short Term Memory (LSTM) with TensorFlow.js framework
Beginner-friendly collection of Python notebooks for various use cases of machine learning, deep learning, and analytics. For each notebook there is a separate tutorial on the relataly.com blog.
A library that unifies the API for most commonly used libraries and modeling techniques for time-series forecasting in the Python ecosystem.
TS-ICL: a Time-Indexed Foundation Model for Time Series Forecasting & Imputation via In-Context Learning
Official implementation of "Time Evidence Fusion Network: Multi-source View in Long-Term Time Series Forecasting" (https://arxiv.org/abs/2405.06419)
🪁 A fast Adaptive Machine Learning library for Time-Series, that lets you build, deploy and update composite models easily. An order of magnitude speed-up, combined with flexibility and rigour. This is an internal project - documentation is not updated anymore and substantially differ from the current API.
X-Trend: Few-Shot Learning Patterns in Financial Time-Series for Trend-Following Strategies
Code for IoTJ 2024 paper "SageFormer: Series-Aware Framework for Long-Term Multivariate Time-Series Forecasting".
Access to Sulie foundation models for time-series forecasting 📈
🔬 A Researcher&Agent-Friendly Framework for Time Series Analysis. Train Any Model on Any Dataset!
[ICML 2024] Official implementation of: "Revitalizing Multivariate Time Series Forecasting: Learnable Decomposition with Inter-Series Dependencies and Intra-Series Variations Modeling".
This repository contains the implementation of paper Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting with different loss functions in Tensorflow. We have compared 14 regression loss functions performance on 4 different datasets.
MFRFNN: Multi-Functional Recurrent Fuzzy Neural Network for Chaotic Time Series Prediction
VMD-MFRFNN
📊 30 Days of Data Science is a daily challenge to guide you through Data Science essentials. From basics to advanced, this repo offers clear examples, practical exercises, and resources to help you master Data Science, one day at a time. Whether you're new or refining your skills, this challenge has something for you. Join the journey now! 🚀
This repository contains the pytorch code for the 2023 ICASSP paper "Preformer: Predictive Transformer with Multi-Scale Segment-wise Correlations for Long-Term Time Series Forecasting”
APDTFlow is a modern and extensible forecasting framework for time series data that leverages advanced techniques including neural ordinary differential equations (Neural ODEs), transformer-based components, and probabilistic modeling. Its modular design allows researchers and practitioners to experiment with multiple forecasting models and easily
This is a repository for collecting papers and code in time series domain.
Time Series Forecasting of Walmart Sales Data using Deep Learning and Machine Learning
The official code implementation for MCI-GRU: Stock Prediction Model Based on Multi-Head Cross-Attention and Improved GRU.
