Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
- forecasting
- r
- python
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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
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
The Time Series Visualization Tool that you deserve.
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
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
The simplest way to group temporal data
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
Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
- deep-learning
- pytorch
- time-series-forecasting
- time-series
Official implementation for "iTransformer: Inverted Transformers Are Effective for Time Series Forecasting" (ICLR 2024 Spotlight)
- time-series-forecasting
- transformer
Open source time series library for Python