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README.md

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+---
+language: en
+tags:
+- cryptocurrency
+- polkadot
+- price-prediction
+- machine-learning
+- time-series
+license: mit
+---
+
+# Polkadot (DOT) Price Prediction Models
+
+Trained ML models for predicting Polkadot (DOT) cryptocurrency prices.
+
+## 📊 Model Performance
+
+| Model | RMSE | MAE |
+|-------|------|-----|
+| Random Forest | 0.2348 | 0.1403 |
+| Gradient Boosting | 0.2031 | 0.1157 |
+| Linear Regression | 0.0200 | 0.0149 |
+| LSTM | 0.2332 | 0.1725 |
+
+## 🎯 Training Details
+
+- **Trained on**: 2025-10-24 07:45:22
+- **Data Source**: CoinGecko API
+- **Historical Days**: 365
+- **Features**: 23 technical indicators
+- **GPU**: Accelerated with TensorFlow
+
+## 📦 Files Included
+
+- `polkadot_sklearn_models.pkl`: Scikit-learn models (RF, GB, LR)
+- `polkadot_scaler.pkl`: Feature scaler
+- `polkadot_lstm_model.h5`: LSTM neural network
+- `polkadot_metadata.json`: Training metadata
+
+## 🚀 Usage
+
+```python
+from huggingface_hub import hf_hub_download
+import joblib
+from tensorflow.keras.models import load_model
+
+# Download models
+sklearn_path = hf_hub_download(
+    repo_id="YOUR_USERNAME/YOUR_REPO",
+    filename="polkadot_sklearn_models.pkl"
+)
+scaler_path = hf_hub_download(
+    repo_id="YOUR_USERNAME/YOUR_REPO",
+    filename="polkadot_scaler.pkl"
+)
+lstm_path = hf_hub_download(
+    repo_id="YOUR_USERNAME/YOUR_REPO",
+    filename="polkadot_lstm_model.h5"
+)
+
+# Load models
+models = joblib.load(sklearn_path)
+scaler = joblib.load(scaler_path)
+lstm = load_model(lstm_path)
+
+# Make predictions
+# (prepare your features first)
+predictions = models['RandomForest'].predict(scaled_features)
+```
+
+## 📈 Features
+
+The models use 23 technical indicators including:
+- Moving Averages (SMA 7, 25, 99)
+- Exponential Moving Averages (EMA 12, 26)
+- RSI (Relative Strength Index)
+- MACD & Signal Line
+- Bollinger Bands
+- Stochastic Oscillator
+- Volatility measures
+- Lag features
+
+## ⚠️ Disclaimer
+
+These models are for educational and research purposes only. Cryptocurrency markets are highly volatile and unpredictable. Do not use these predictions for actual trading decisions without proper risk management.
+
+## 📄 License
+
+MIT License