📈 Bitcoin Price Prediction Dashboard (2014-2023)

Daily OHLCV Time Series Analysis & ML Forecasting

🎯 Project Overview

9+ years (2014-2023) Bitcoin historical data end-to-end ML pipeline created:

• 📊 EDA: Price trends, volatility analysis, volume patterns
• ⚙️ Features: Technical indicators (RSI, Moving Averages, Lags)
• 🤖 Model: Random Forest Regressor (Test RMSE: $XXX)
• 📱 Deployment: Interactive Streamlit dashboard

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📊 Key Results

Metric	Value
Dataset	3,300+ days
Test RMSE	$XXX (XX.XX%)
Top Feature	Lag1 Close (XX.XX%)
Time Period	Sep 2014 - Dec 2023

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🛠️ Tech Stack

Pandas -  Scikit-learn -  Matplotlib -  Seaborn -  Streamlit
Random Forest -  RSI -  Moving Averages -  Time Series


bitcoin-price-prediction/
│
├── README.md                    # Project documentation
├── notebook/
│   └── Bitcoin_Analysis.ipynb   # Complete Kaggle notebook
├── data/
│   └── bitcoin-1.csv           # 3.3K rows OHLCV data
├── models/
│   └── rf_model.pkl            # Trained Random Forest
├── app.py                      # Streamlit dashboard
├── requirements.txt            # Dependencies
└── screenshots/                # Results images