Awesome GitHub RepositoriesData Loaders

This project is a comprehensive platform for quantitative investment research, machine learning, and algorithmic trading. It provides an end-to-end environment for developing, testing, and executing financial strategies, supporting the entire lifecycle from data ingestion and feature engineering to model training and backtesting. The system is distinguished by its configuration-driven workflow orchestration, which allows researchers to automate complex pipelines and manage experiments through declarative files. It features a high-performance data infrastructure that utilizes custom binary for

GraphQL.NET 是一个用于在 C# 应用程序中构建和执行 GraphQL API 的服务端框架。它提供了一套全面的工具包，用于模式构建、分布式数据图的联合引擎，以及用于管理实时数据流的订阅处理器。 该项目的独特之处在于其灵活的模式构建器，支持程序化的代码优先定义和使用标准模式定义语言的声明式模式优先方法。它包括一个专门的联合引擎，用于将数据图拆分为子图并将其组合成统一的网关，以及一个专门设计用于通过批处理和缓存解决 N+1 查询问题的数据加载器实现。 该框架涵盖了广泛的操作功能，包括用于服务生命周期管理的依赖注入集成、用于字段解析拦截的中间件流水线，以及针对值类型优化以减少内存分配的执行流水线。它还提供用于查询复杂度分析、文档缓存和基于角色的访问控制的工具，以保护 API 端点。 对提前（AOT）模式编译的支持允许该框架在禁止动态代码生成的环境中执行。

This is a structured deep learning curriculum for programmers, delivered as a collection of Jupyter notebooks. It teaches the fundamentals of training neural networks for computer vision, natural language processing, tabular data analysis, and collaborative filtering using PyTorch and the fastai library. The course is designed to be hands-on, guiding learners from building a training loop from scratch to fine-tuning pretrained models for a variety of practical tasks. The curriculum distinguishes itself by covering the full lifecycle of a deep learning project, from data preparation and augmen