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crypto-analysis

Here are 28 public repositories matching this topic...

AML Checker detection and analysis tools for cryptocurrency transactions using machine learning and blockchain data. Ensuring compliance and reducing money laundering risks.

  • Updated May 31, 2025
crypto-aml-check

AML Checker detection and analysis tools for cryptocurrency transactions using machine learning and blockchain data. Ensuring compliance and reducing money laundering risks.

  • Updated Feb 27, 2025

FibScout is a Python-based tool for advanced cryptocurrency analysis. It uses real-time data from ccxt.gate(), applies the Awesome Oscillator and Fibonacci retracement levels, and delivers instant Telegram alerts. Designed for efficient market monitoring, it supports asynchronous execution and seamless deployment on platforms like Railway.

  • Updated Mar 13, 2025
  • Python

open source crypto currency exchange platform, bitcoin exchange based on Java | BTC exchange | ETH exchange | digital currency exchange | trading platform | matching trading engine,Sniper Bot.Secure multi crypto exchange trading client.powerful, fast and easy to use .NET/C# API for interfacing with many crypto currency exchanges.

  • Updated Jun 2, 2025
  • C#

open source crypto currency exchange platform, bitcoin exchange based on Java | BTC exchange | ETH exchange | digital currency exchange | trading platform | matching trading engine,Sniper Bot.Secure multi crypto exchange trading client.powerful, fast and easy to use .NET/C# API for interfacing with many crypto currency exchanges.

  • Updated May 29, 2025

open source crypto currency exchange platform, bitcoin exchange based on Java | BTC exchange | ETH exchange | digital currency exchange | trading platform | matching trading engine,Sniper Bot.Secure multi crypto exchange trading client.powerful, fast and easy to use .NET/C# API for interfacing with many crypto currency exchanges.

  • Updated Mar 4, 2025
  • C#

This project performs exploratory data analysis (EDA) on historical cryptocurrency data. The goal is to analyze price trends, volatility, and patterns in the market using data visualization techniques. The project uses Python libraries such as Pandas, Matplotlib, and Seaborn for analysis and visualization.

  • Updated Apr 7, 2025
  • Jupyter Notebook

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