TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.
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Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
- forecasting
- r
- python
Statsmodels: statistical modeling and econometrics in Python
- python
- statistics
- econometrics
- data-analysis
Fast and Accurate ML in 3 Lines of Code
A unified framework for machine learning with time series
- time-series
- machine-learning
- scikit-learn
- time-series-classification
A python library for user-friendly forecasting and anomaly detection on time series.
- python
- time-series
- forecasting
- machine-learning
The GitHub repository for the paper "Informer" accepted by AAAI 2021.
- deep-learning
- self-attention
- time-series
- pytorch
Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.
Numenta Platform for Intelligent Computing is an implementation of Hierarchical Temporal Memory (HTM), a theory of intelligence based strictly on the neuroscience of the neocortex.
- neocortex
- artificial-intelligence
- machine-intelligence
- hierarchical-temporal-memory
Chronos: Pretrained Models for Time Series Forecasting
- forecasting
- large-language-models
- llm
- machine-learning
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
- time-series-classification
- deep-learning
- fastai
- pytorch
Probabilistic time series modeling in Python
- time-series
- deep-learning
- forecasting
- neural-networks
Technical Analysis Library using Pandas and Numpy
- trading
- technical-analysis
- python3
- volume
Time series forecasting with PyTorch
Lightning ⚡️ fast forecasting with statistical and econometric models.
- time-series
- statistics
- forecasting
- arima
Scalable and user friendly neural :brain: forecasting algorithms.
- deep-learning
- forecasting
- esrnn
- nbeats
NeuralProphet: A simple forecasting package
- forecasting
- time-series
- machine-learning
- fbprophet
STUMPY is a powerful and scalable Python library for modern time series analysis
- data-science
- time-series-analysis
- dask
- numba
TimeGPT-2.1: 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 🚀.
- time-series
- time-series-forecasting
- deep-learning
- forecasting
Python AutoML toolkit for benchmarking classification, regression, and time-series forecasting models, with GPU acceleration, MLflow tracking, and automated preprocessing.
- machine-learning
- automl
- regression
- classification
The machine learning toolkit for time series analysis in Python
- time-series
- timeseries
- time-series-analysis
- time-series-clustering
An offical implementation of PatchTST: "A Time Series is Worth 64 Words: Long-term Forecasting with Transformers." (ICLR 2023) https://arxiv.org/abs/2211.14730
[ICLR 2024] Official implementation of " 🦙 Time-LLM: Time Series Forecasting by Reprogramming Large Language Models"
- cross-modal-learning
- cross-modality
- deep-learning
- language-model
[AAAI-23 Oral] Official implementation of the paper "Are Transformers Effective for Time Series Forecasting?"
- deep-learning
- forecasting
- forecasting-model
- linear-models