Open-source alternatives to Mcp Server Data Exploration

This repository is a comprehensive collection of instructional guides and practical examples for Python development, focusing on machine learning, data science, and web scraping. It provides implementations for neural networks, reinforcement learning algorithms, and deep learning architectures using PyTorch, alongside detailed manuals for scientific computing and data visualization. The project distinguishes itself by offering specialized tutorials on concurrent programming to optimize CPU performance and guides for setting up Linux development environments. It covers the implementation of ad

This project provides a suite of interfaces and tools for accessing electricity carbon intensity and production metrics. It includes an API for real-time and historical data, a geographic power data map for visualizing regional carbon intensity and renewable energy percentages, and a system for extracting datasets required for standardized greenhouse gas emissions reporting. The project features an interactive API sandbox that allows users to test requests and inspect data responses without writing code. It also includes mechanisms for institutional email verification to manage access to hist

This project is a comprehensive technical reference and programming cheatsheet for the Python language. It serves as a curated catalog of language features, syntax patterns, and standard library functions designed to help developers identify and apply correct coding patterns. The documentation covers a broad range of functional areas, including language fundamentals such as object-oriented structuring, functional logic, and list comprehensions. It also provides guidance on utilizing the standard library for data analysis, file management, networking, and concurrent execution. The reference e

This project is a collection of educational resources and reference implementations for neural network development using TensorFlow. It serves as a comprehensive learning course, machine learning curriculum, and practical implementation guide for building deep learning architectures. The codebase provides instructional materials and examples covering a wide range of model types, including convolutional neural networks for image classification, recurrent networks and long short-term memory cells for sequential data, and autoencoders for generative modeling. It also includes implementations for

Machine Learning Yearning book by 🅰️𝓷𝓭𝓻𝓮𝔀 🆖

Reinforcement learning resources curated

Ruby - R bridge.

A list of awesome tools, ideas, prompt engineering tools, colabs, models, and helpers for the prompt designer playing with aiArt and image synthesis. Covers Dalle2, MidJourney, StableDiffusion, and open source tools.

Aye Chat: AI-powered terminal workspace

Open coding agent, provider agnositc.

FinRL is a financial reinforcement learning framework and quantitative trading library. It provides a specialized system for developing, training, and simulating autonomous agents designed to automate financial trading and portfolio management. The project serves as an automated portfolio optimizer and financial market simulator. It enables the creation of decision-making policies to balance asset allocations, maximize potential returns, and minimize financial risk through reinforcement learning. The framework includes capabilities for financial market data engineering, algorithmic trading s

acl-release-shield: https://img.shields.io/badge/version-53.1.0-green acl-release: https://github.com/ARM-software/ComputeLibrary/releases/v53.1.0

Zsh plugin that integrates Claude Code CLI into your shell. Chat with Claude and execute AI-generated commands directly from your terminal prompt

Agentset MCP Server - Build RAG with Agentic superpowers

Stable Diffusion Web UI is a browser-based interface designed for managing text-to-image generation tasks. It provides a centralized dashboard for controlling generative processes, including native support for multi-stage model architectures to facilitate high-quality image refinement. The platform distinguishes itself through granular control over the generation process, offering tools for precise parameter management and advanced prompt engineering. Users can customize generation styles and capabilities by integrating external model-extension formats, such as textual inversions, low-rank ad

Axiom Model Context Protocol Server

Utilities and scripts developed as part of Microsoft's Team Data Science Process for productive data science

High-performance time-series database built on DuckDB. Go implementation.

A curated list of community detection research papers with implementations.

A collection of research papers on decision, classification and regression trees with implementations.

A curated list of data mining papers about fraud detection.

Let AI agents message, watch, and spawn each other across terminals. Claude Code, Codex, Antigravity CLI, Cursor CLI, OpenCode, Kilo, Pi, Kimi