6 个仓库
Tools that allow training, deployment, and inference of machine learning models using standard SQL syntax.
Distinguishing note: Focuses on the SQL interface for ML operations, distinct from programmatic SDK-based model management.
Explore 6 awesome GitHub repositories matching artificial intelligence & ml · SQL-Based Machine Learning. Refine with filters or upvote what's useful.
Minds Platform is an automation system and application platform designed for building and deploying custom AI tools and workflows. It functions as a machine learning integration layer and self-hosted orchestrator that connects predictive models and large language models to external data sources. The platform enables the execution of multi-step tasks that read and write data to automate reports and operational activities. It supports deployment across cloud, on-premises, and virtual private cloud environments to maintain control over models and data. Capabilities include event-driven workflow
Exposes machine learning model capabilities through standard SQL queries for simplified data analysis.
MindsDB is an AI-native database engine that treats machine learning models and autonomous agents as virtual tables. By mapping external data sources, predictive models, and third-party services directly into the database schema, it enables users to perform inference, data retrieval, and complex orchestration using standard SQL syntax. The platform distinguishes itself through an autonomous agent orchestrator that executes iterative reasoning loops, allowing agents to plan data access and synthesize natural language responses from connected knowledge bases. It functions as a federated data ga
Training, deploying, and querying predictive models as virtual database tables to simplify the integration of AI into applications.
This is a reference implementation library providing a collection of code samples, Transact-SQL scripts, and schemas for SQL Server, Azure SQL, and Azure Synapse. It focuses on providing standardized implementation patterns and reference code for building relational databases and cloud data warehouses. The library distinguishes itself by offering specialized guides and examples for deploying database instances within containerized environments and Azure cloud services. It includes specific reference databases and language extensions for integrating machine learning services and advanced analy
Implements machine learning services and advanced analytics by integrating external language runtimes directly within the database engine.
PostgresML is a machine learning database extension for PostgreSQL that integrates model training and inference directly into the database. It functions as an in-database AI platform and vector database, enabling the execution of large language models and natural language processing tasks on stored records without exporting data to external services. The system distinguishes itself by utilizing GPU acceleration to minimize latency during model predictions and employing a hybrid storage engine that maintains relational data alongside high-dimensional vectors. It allows for the building and fin
Trains machine learning models directly via database queries to eliminate the need for exporting data to external environments.
pgai 是一个 PostgreSQL AI 工具包和框架,旨在将大语言模型和向量嵌入直接集成到数据库中。它充当了在标准数据库查询中执行机器学习模型请求和进行文本转 SQL 翻译的桥梁。 该项目提供了一个自动化的向量嵌入流水线,负责处理来自表和非结构化文档的文本加载、解析和分块。该系统利用后台工作进程在源数据发生变化时自动同步嵌入,并包含用于构建检索增强生成(RAG)应用和语义搜索引擎的专用工具。 该工具包涵盖了广泛的功能领域,包括利用 OCR 处理非结构化数据、创建将数据库模式映射到自然语言的语义目录,以及通过向量索引和结果重排序实现高性能相似度搜索。它还支持通过 SQL 调用外部模型,从而实现数据增强、分类和内容审核。
Enables executing machine learning model requests and inference directly within standard SQL queries.
sqlflow 是一个 SQL 机器学习引擎与编排器,旨在通过扩展的 SQL 查询语法来训练、部署与解释机器学习模型。它通过将数据库引擎连接到外部机器学习工具包,实现了数据库内机器学习,允许用户直接通过查询定义训练数据集与超参数。 该系统作为预测接口与可解释性工具运行。它允许通过在标准 SQL 语句中调用模型函数,对数据库记录生成分类与预测,并提供了一个工作流来解释特定特征如何影响模型决策。
Defines machine learning training and inference parameters using a custom SQL query syntax.