Kronos: A Foundation Model for the Language of Financial Markets
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TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.
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
Automatic extraction of relevant features from time series:
- data-science
- feature-extraction
- time-series
The GitHub repository for the paper "Informer" accepted by AAAI 2021.
- deep-learning
- self-attention
- time-series
- pytorch
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
The Time Series Visualization Tool that you deserve.
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
Lightning ⚡️ fast forecasting with statistical and econometric models.
- time-series
- statistics
- forecasting
- arima
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
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
- pytorch
- graph-neural-networks
- temporal-networks
- temporal-graphs
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
About Code release for "Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting" (NeurIPS 2021), https://arxiv.org/abs/2106.13008