Awesome GitHub RepositoriesMultivariate Series Alignment

GluonTS is a framework for probabilistic time series forecasting, designed to predict future values as probability distributions with confidence intervals. It supports both traditional model training and zero-shot forecasting, where pretrained models generate predictions for new series without additional training. The project distinguishes itself by integrating a wide variety of forecasting approaches into a unified workflow. This includes deep learning architectures such as recurrent neural networks and causal convolutions, as well as the integration of external statistical models, the Proph

GluonTS 是一个概率时间序列库和深度学习预测框架。它提供了一套工具包，用于构建、训练和评估神经网络架构，通过将未来值预测为概率分布来量化不确定性。 该项目的独特之处在于支持零样本（zero-shot）预测，并集成了多种建模方法，包括深度概率神经网络以及对 Prophet 和 R forecast 等外部统计库的封装。它实现了因果卷积和可逆残差网络等专门的架构原语，以防止信息泄露并将潜在表示映射为有效的概率分布。 该框架涵盖了全面的数据工程功能，包括时间序列缩放、双射变换和分层建模。它利用 Apache Arrow 和 Parquet 进行高性能数据集流式传输和随机访问管理。在模型评估方面，它包含一套评估套件，使用分位数损失（quantile loss）和连续排名概率分数（CRPS）等指标来衡量预测准确性和概率覆盖率。 该库支持通过集成 Amazon SageMaker 进行模型部署。

pyalgotrade is a Python algorithmic trading library designed for developing, backtesting, and executing automated trading strategies. It provides a comprehensive framework for financial strategy backtesting, a technical analysis library for computing mathematical indicators, and connectors for cryptocurrency exchange integration. The project distinguishes itself by supporting sentiment-based trading through the integration of real-time social media feeds and keyword streams. It features a quantitative trading visualization tool for plotting price action and portfolio equity curves, along with