30 open-source projects similar to alexgutteridge/rsruby, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Rsruby alternative.
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 repository serves as an educational collection of interactive notebooks and code examples designed to demonstrate fundamental machine learning and deep learning concepts. It provides a structured environment for exploring data science workflows, ranging from basic numerical computing and statistical analysis to the construction of complex neural network architectures. The project distinguishes itself through a focus on hands-on experimentation, offering practical implementations for tasks such as computer vision, natural language processing, and statistical simulation. Users can engage w
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 collection of educational notes and tutorials focused on Python programming, scientific computing, and data analysis. It serves as a reference for learning language basics, advanced techniques, and object-oriented design. The materials include implementation guides for building linear, logistic, and convolutional neural networks using symbolic graph frameworks. It also provides instruction on manipulating and visualizing structured data frames and performing complex mathematical operations through numerical libraries. The repository includes a system for converting interact
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
Utilities and scripts developed as part of Microsoft's Team Data Science Process for productive data science
MCP Server for Chronulus AI Forecasting and Prediction Agents
Model Context Protocol (MCP) implementation for Opik enabling seamless IDE integration and unified access to prompts, projects, traces, and metrics.
An unofficial fork of the Ruby graphing library with sexy defaults for hi-res charts. (NOT MAINTAINED)
ADAM is a genomics analysis platform with specialized file formats built using Apache Avro, Apache Spark, and Apache Parquet. Apache 2 licensed.
ParaMonte: Parallel Monte Carlo and Machine Learning Library for Python, MATLAB, Fortran, C++, C.
MCP server for managing and interacting with Flowcore Platform
Perspective is a columnar data analytics library and streaming data visualization engine. It provides an interactive data grid component and notebook analytics widgets designed for processing high-volume data and rendering interactive charts and grids. The system utilizes a high-performance query engine to enable real-time data analysis and streaming dataset visualization. It supports the creation of customizable dashboards and reports that update automatically as new data arrives without requiring full dataset reloads. The project covers large-scale dataset analytics through a schema-driven
Crafty statistical graphics for Julia.
A Model Context Protocol server for generating charts using QuickChart.io . It allows you to create various types of charts through MCP tools.
A Model Context Protocol (MCP) server for GreptimeDB
This project is a Model Context Protocol server that provides an interface for AI agents to programmatically create, read, and modify Excel workbooks. It serves as a bridge that enables large language models to perform spreadsheet automation and data visualization. The server allows AI agents to generate native Excel charts and pivot tables from raw data, transforming structured information into visual summaries. It provides a mechanism for remote spreadsheet management through a protocol-based connectivity layer. The system covers a broad range of spreadsheet manipulation capabilities, incl
A Model Context Protocol (MCP) server implementation that provides the LLM an interface for visualizing data using Vega-Lite syntax.