statsforecast
Time series forecaster
An implementation of widely used time series forecasting models in Python
Lightning ⚡️ fast forecasting with statistical and econometric models.
4k stars
41 watching
283 forks
Language: Python
last commit: 10 days ago
Linked from 1 awesome list
arimaautomlbaselinesdata-scienceeconometricsetsexponential-smoothingfbprophetforecastingmachine-learningmstlnaiveneuralprophetpredictionsprophetpythonseasonal-naivestatisticsthetatime-series
krzjoa/awesome-python-data-scienceRelated projects:
| Repository | Description | Stars |
|---|---|---|
| nixtla/neuralforecast | An open-source Python library providing a unified interface to various neural forecasting models, focusing on performance, usability, and robustness. | 3,101 |
| nixtla/mlforecast | A Python library for scalable machine learning-based time series forecasting with efficient feature engineering and out-of-the-box compatibility. | 899 |
 skforecast/skforecast | A Python library for building machine learning models to forecast time series data | 1,156 |
 awslabs/gluonts | A Python package for building probabilistic models of time series data using deep learning techniques. | 4,629 |
 sktime/pytorch-forecasting | A PyTorch-based package for state-of-the-art time series forecasting with deep learning architectures | 4,001 |
 statsmodels/statsmodels | Provides a comprehensive set of statistical modeling tools and techniques for data analysis and interpretation in Python. | 10,151 |
 timeseriesai/tsai | A comprehensive deep learning package for time series data analysis and forecasting. | 5,262 |
 automl/auto-pytorch | An automatic deep learning framework that jointly optimizes network architecture and training hyperparameters. | 2,376 |
 blue-yonder/tsfresh | An automated feature extraction tool for time series data, removing irrelevant features and improving machine learning model performance. | 8,435 |
 unit8co/darts | A Python library for user-friendly time series forecasting and anomaly detection | 8,087 |
 facebook/prophet | An automatic forecasting procedure for time series data with multiple seasonality and linear or non-linear growth | 18,514 |
 doi-bor/pyforecast | Tools for building predictive models of seasonal water flow and inflow forecasts | 28 |
 microsoft/flaml | Automates machine learning workflows and optimizes model performance using large language models and efficient algorithms | 3,919 |
 vaexio/vaex | A high-performance Python library for streaming and exploring large tabular datasets. | 8,297 |
 pydantic/pydantic | A Python library for validating data using type hints and JSON Schema. | 21,145 |