Real-Time Crpto Market Regime Classification with Deep Learning ========================================================= A sophisticated, real-time pipeline that uses a multi-timeframe LSTM model to classify cryptocurrency market behavior (e.g., Trend, Range, Volatility Spike) for BTCUSDT, providing live predictions every minute. About This Project This repository contains the complete code for a live inference pipeline that classifies the current market regime of BTCUSDT. The system fetches live data from Binance, processes it through a feature engineering pipeline that considers multiple timeframes (5m, 15m, 1h), and feeds the result into a trained LSTM (Long Short-Term Memory) neural network. The primary goal is to provide a continuous, real-time signal that can be used to inform algorithmic trading strategies, risk management systems, or market analysis dashboards. For example, a trading algorithm might only take trend-following entries when the model predicts a Strong Trend regime, or tighten stop-losses when a Volatility Spike is predicted. 🔑 Key Features --------------- Real-

⚠ No verified equity curve — no track-record source connected.

No score history is stored yet — only the current score is shown.

⚠ No live verification account connected — ask for proof before buying.

Alerts on changes: coming soon

Prop-firm compatibility not provided.

Data-completeness & trust index (not a profitability rating)