allen-chiang/Time-Series-Transformer
A data preprocessing package for time series data. Design for machine learning and deep learning.
Time Series Transformer helps data scientists and analysts prepare their time-series data for machine learning and deep learning models. It takes raw time-series datasets, potentially with categories like product names or stock tickers, and outputs transformed data with added features like lagged or leading values and sequences. This tool is designed for anyone building predictive models on sequential data, such as financial forecasting or inventory management.
216 stars. No commits in the last 6 months.
Use this if you need to easily create features like time lags, leads, or sequences from your time-series data to feed into machine learning models.
Not ideal if you primarily need advanced statistical analysis, complex forecasting models, or interactive visualizations for time series data.
Stars
216
Forks
37
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jan 18, 2021
Commits (30d)
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