Bitcoin Price Predictor

The Bitcoin Price Predictor is a machine learning project designed to forecast Bitcoin's future prices using historical market data. With the high volatility in the cryptocurrency market, accurately predicting price trends can provide valuable insights for investors and traders.

💡 Inspiration The project was inspired by the growing relevance of cryptocurrencies and the challenge of making sense of unpredictable price swings. I wanted to explore whether machine learning could detect patterns in Bitcoin’s movement and deliver actionable insights.

🛠️ How I Built It I collected historical price data (Open, High, Low, Close, Volume) and engineered features like moving averages and price changes. After cleaning and normalizing the dataset, I implemented models such as Linear Regression, Support Vector Regression (SVR), and LSTM Neural Networks for time-series forecasting. Performance was evaluated using metrics like RMSE and R² Score, and visualizations were created to compare predicted vs. actual prices.

📚 What I Learned This project enhanced my understanding of time-series forecasting, feature engineering, and the differences between traditional ML and deep learning in financial contexts. I also deepened my grasp of hyperparameter tuning and model evaluation techniques.

🧩 Challenges Key challenges included handling noisy, volatile data and preventing overfitting. Selecting the right model architecture and determining the appropriate time granularity (daily vs. hourly) also required careful experimentation.

🎯 Outcome The project successfully demonstrated that machine learning models can capture trends in Bitcoin pricing, providing a strong foundation for future exploration in crypto forecasting.

Built With

• csv
• kaggle
• matpilotlab
• numpy
• pandas
• python
• schikit
• scikit-learn
• svm
• tensorflow