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Source channel @githubtrending · Post #14933 · Jul 9
#go#databases#genai#llms#mcp The MCP Toolbox for Databases helps developers connect AI agents to databases more easily and securely. It simplifies the process by handling complex tasks like connection pooling and authentication, allowing you to integrate databases with AI agents using minimal code. This toolbox supports the Model Context Protocol (MCP), which standardizes how AI interacts with external tools. By using MCP Toolbox, you can automate database tasks, query databases using natural language, and generate context-aware code, all of which save time and improve development efficiency. https://github.com/googleapis/genai-toolbox
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@repo_science · Post #3807 · 12/19/2023, 05:08 AM
#AutoML 🐍 AutoML: Build Production-Ready Models Quickly! Learn the basics of building production-ready automated machine learning (AutoML) models. ----- Main channel: @repo_science Coupons: @freecoupons_reposcience -----
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@githubtrending · Post #14863 · 06/24/2025, 01:30 PM
#other#automl#chatgpt#data_analysis#data_science#data_visualization#data_visualizations#deep_learning#gpt#gpt_3#jax#keras#machine_learning#ml#nlp#python#pytorch#scikit_learn#tensorflow#transformer This is a comprehensive, regularly updated list of 920 top open-source Python machine learning libraries, organized into 34 categories like frameworks, data visualization, NLP, image processing, and more. Each project is ranked by quality using GitHub and package manager metrics, helping you find the best tools for your needs. Popular libraries like TensorFlow, PyTorch, scikit-learn, and Hugging Face transformers are included, along with specialized ones for time series, reinforcement learning, and model interpretability. This resource saves you time by guiding you to high-quality, actively maintained libraries for building, optimizing, and deploying machine learning models efficiently. https://github.com/ml-tooling/best-of-ml-python