Exohood Labs's Projects
🌏 Bitcoin.org Website
📌Utility for detecting phishing domains targeting Ethereum users
🔑A collection of functions for signing and verifying data with Ethereum keys.
Specification for the Execution Layer. Tracking network upgrades.
📚Remix is a browser-based compiler and IDE that enables users to build Ethereum contracts with Solidity language and to debug transactions.
⛓Common tests for all Ethereum implementations.
📚A library for generating Etherscan links
🎨Image tracking, Location Based AR, Marker tracking. All on the Web.
📚Open source, production ready animation and gesture library for React
💾 Join the Blockchain Revolution! Contribute, collaborate, and build the future of blockchain technology with Eureka Software.
😎 Streaming server for Unity
🎓 EurekaVR
🤖Get Started Building with Generative AI
🧠Granite Code Models: A Family of Open Foundation Models for Code Intelligence
🧠Kusto Query Language is a simple and productive language for querying Big Data.
🧠 Exania AI Learning is the process of determining the independent, actual effect of a particular phenomenon that is a component of a larger system.
🤖 User behavior prediction from event data.
🤖Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
📘Q# compiler, command line tool, and Q# language server
📚Official repository for design of the quantum programming language Q# and its core libraries
🤖 Integrating quantum computing with Exania AI for enhanced data processing, accelerated learning and robust blockchain security.
⚙️Microsoft Quantum Development Kit Samples
🤖Hybrid Quantum Classical Machine Learning in TensorFlow
📚Tutorials and programming exercises for learning Q# and quantum computing
🤖scikit-learn: machine learning in Python
🤖Deep and online learning with spiking neural networks in Python
🤖 An experimental AI powered Telegram bot, designed to engage users with concise, witty responses across a broad spectrum of knowledge including STEM, blockchain, and more, leveraging continuous learning from diverse web resources.
🤖This Python package is designed for mapping the solution space of machine learning models. An understanding of the organisation of the solution space can answer important questions about the reproducibility, explainability and performance of ML methods.