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东流TFTS (TensorFlow Time Series) 是基于TensorFlow时间序列开源工具，支持多种深度学习模型
- 结构灵活，适配多种时间序列任务
- 多套久经考验的深度学习模型
- 查阅文档，快速入门
中文名“东流”，源自辛弃疾“青山遮不住，毕竟东流去。江晚正愁余，山深闻鹧鸪”。
安装
pip install tensorflow>=2.0.0
pip install tfts
快速使用
import tensorflow as tf
import tfts
from tfts import AutoModel, KerasTrainer
train, valid = tfts.load_data('sine')
backbone = AutoModel('seq2seq')
model = functools.partial(backbone.build_model, input_shape=[24, 2])
trainer = KerasTrainer(model)
trainer.train(train, valid)
trainer.predict(valid[0])
示例
- 东流Bert模型 获得KDD CUP2022百度风机功率预测第3名
- 东流Seq2seq模型 获得阿里天池-AI earth人工智能气象挑战赛第4名
更多应用
- Time_series_prediction
- Time series classification
- Anomaly detection
- Uncertainty prediction
- Parameters tuning with optuna
引用
@misc{tfts2020,
author = {Longxing Tan},
title = {Time series prediction},
year = {2020},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/longxingtan/time-series-prediction}},
}
