Auto_TS
tsai
| Auto_TS | tsai | |
|---|---|---|
| 6 | 4 | |
| 673 | 4,703 | |
| - | 2.5% | |
| 6.9 | 7.4 | |
| 3 months ago | 13 days ago | |
| Jupyter Notebook | Jupyter Notebook | |
| Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Auto_TS
tsai
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Aeon: A unified framework for machine learning with time series
Also https://github.com/timeseriesAI/tsai
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What is the current state-of-art in sequence classification?
You might be interested in tsai. I am not affiliated with them and have not used tsai, but I have been planning to try it for too long … well :p
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[P] Deep Learning for time series forecasting (neuralforecast, python package)
how about tsai?
- Machine learning with Time series data
What are some alternatives?
Deep_XF - Package towards building Explainable Forecasting and Nowcasting Models with State-of-the-art Deep Neural Networks and Dynamic Factor Model on Time Series data sets with single line of code. Also, provides utilify facility for time-series signal similarities matching, and removing noise from timeseries signals.
darts - A python library for user-friendly forecasting and anomaly detection on time series.
Auto_ViML - Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
sktime-dl - DEPRECATED, now in sktime - companion package for deep learning based on TensorFlow
modeltime - Modeltime unlocks time series forecast models and machine learning in one framework
statsforecast - Lightning ⚡️ fast forecasting with statistical and econometric models.
ChatLog - ⏳ ChatLog: Recording and Analysing ChatGPT Across Time
flow-forecast - Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
neuralforecast - Scalable and user friendly neural :brain: forecasting algorithms.
logbrain - Parsing log files can be a tedious task, especially when dealing with complex log formats. The Log Parser aims to streamline this process by leveraging regular expressions to match and capture relevant fields from log entries. With the extracted data, users can perform further analysis, generate reports, or gain insights from their log files.
nixtla - Python SDK for TimeGPT, a foundational time series model