Machine Learning–Based Crypto Trading Signal Platform
AI-powered cryptocurrency trading platform generating real-time signals using LSTM and Random Forest models.
Overview
An AI-powered cryptocurrency trading platform that generates real-time trading signals using machine learning models. The system analyzes BTC/USDT market data with LSTM neural networks and Random Forest models, and presents insights through an interactive React-based dashboard.
The Problem
Crypto markets are highly volatile and require: Timely analysis of price movements • Signal generation based on historical and real-time data • Clear visualization of indicators and trends • Low-latency updates for decision-making Manual analysis struggles to scale across multiple assets and short timeframes.
The Solution
Machine learning pipeline combining LSTM (temporal patterns) and Random Forest (feature-based signals) • REST API for model inference and data delivery • WebSocket-based live updates for near real-time market refresh • React frontend with candlestick charts and technical indicators
Key Features
- ▸ML-based trading signal generation (LSTM + Random Forest)
- ▸BTC/USDT price movement analysis and predictions
- ▸Real-time market data for top 20 cryptocurrencies
- ▸Automatic updates every 3 minutes
- ▸Interactive candlestick charts with technical indicators
- ▸Responsive React UI for desktop and mobile
Architecture
Backend: Python ML services (TensorFlow), REST API • Models: LSTM for sequence modeling, Random Forest for classification/regression • Frontend: React, JavaScript, Chart.js • Realtime: WebSocket for live market updates • Data: Market price feeds and derived technical features
My Contribution
Designed and implemented the ML pipeline using LSTM and Random Forest • Built the REST API for signal generation and data access • Integrated WebSocket-based live data updates • Developed the React frontend with interactive charts and indicators • Connected model outputs to a user-facing trading signal dashboard