The Python ecosystem offers a rich suite of libraries for time series forecasting. Each caters to different needs and comes with its community and popularity, often reflected in the number of GitHub stars. Here’s a rundown of the top libraries, their best use cases, and resources for learning more:
- Prophet (Facebook):
- Best for: Business forecasting with seasonal patterns and holiday effects.
- GitHub Stars: Check Latest
- Best Articles: Machine Learning Mastery Guide, Digital Ocean Tutorial
- pmdarima:
- Best for: Univariate time series forecasting with ARIMA models.
- GitHub Stars: Check Latest
- Best Articles: Towards Data Science Introduction, Pluralsight’s Advanced Modeling Guide
- Skforecast:
- Best for: Integrating with scikit-learn for robust time series forecasting.
- GitHub Stars: Check Latest
- Best Articles: Prog.world Practical Guide, Towards Data Science Model Evaluation
- Greykite (LinkedIn):
- Best for: Detailed and interpretable forecasting where model understanding is important.
- GitHub Stars: Check Latest
- Best Articles: InfoQ Coverage, LinkedIn Engineering Blog
- Functime:
- Best for: Machine learning at scale, especially for large time series datasets.
- GitHub Stars: Check Latest
- Best Articles: functime Official Site, functime Developer Guide
- Arch:
- Best for: Financial econometrics, particularly for modeling volatility in financial markets.
- GitHub Stars: Check Latest
- Best Articles: Machine Learning Mastery on ARCH/GARCH, Read the Docs for arch
Nixtla’s Suite:
- StatsForecast:
- Best for: Rapid computations and high-performance univariate time series forecasting.
- GitHub Stars: Check Latest
- Best Article: Nixtla Official Page
- mlforecast:
- Best for: Distributed computing environments needing feature engineering at scale.
- GitHub Stars: Check Latest
- NeuralForecast:
- Best for: Leveraging neural networks for time series forecasting, suitable for non-experts.
- GitHub Stars: Check Latest
Transformers for Time Series:
- Best for: State-of-the-art time series forecasting, particularly for complex multivariate series.
- GitHub Stars: Check Latest
- Best Articles: Hugging Face Blog on Transformers, Towards Data Science PyTorch Guide
This curated guide aims to illuminate the path for those exploring the varied landscape of time series forecasting, providing a compass to the tools that resonate most with your project.