TimeSynth
tsai
| TimeSynth | tsai | |
|---|---|---|
| 1 | 4 | |
| 327 | 4,703 | |
| 0.9% | 2.5% | |
| 0.0 | 7.4 | |
| 6 months ago | 13 days ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | 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.
TimeSynth
-
What is the best way to generate synthetic OHLC data?
I have the same question so I cant give a direct answer. However, I've been thinking of using SDV and TimeSynth python packages to produce synthetic data for backtesting.
tsai
-
Aeon: A unified framework for machine learning with time series
Also https://github.com/timeseriesAI/tsai
-
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
-
[P] Deep Learning for time series forecasting (neuralforecast, python package)
how about tsai?
- Machine learning with Time series data
What are some alternatives?
tsfresh - Automatic extraction of relevant features from time series:
darts - A python library for user-friendly forecasting and anomaly detection on time series.
SDV - Synthetic data generation for tabular data
sktime-dl - DEPRECATED, now in sktime - companion package for deep learning based on TensorFlow
ta - Technical Analysis Library using Pandas and Numpy
statsforecast - Lightning ⚡️ fast forecasting with statistical and econometric models.
tempo - API for manipulating time series on top of Apache Spark: lagged time values, rolling statistics (mean, avg, sum, count, etc), AS OF joins, downsampling, and interpolation
flow-forecast - Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
stingray - Anything can happen in the next half hour (including spectral timing made easy)!
neuralforecast - Scalable and user friendly neural :brain: forecasting algorithms.
pycaret - An open-source, low-code machine learning library in Python
nixtla - Python SDK for TimeGPT, a foundational time series model