Built a linear regression model to predict the closing price of a cryptocurrency based on historical price data from the Bitstamp exchange. Cleaned and preprocessed the data, and engineered several features including moving averages and exponential moving averages. Split the data into training and testing sets and used the scikit-learn library in Python to build and evaluate the model. Achieved a mean squared error of X and an R-squared score of Y on the test set.
Skills/Tools used: Python, Pandas, NumPy, Scikit-learn, Linear Regression, Data Cleaning, Data Preprocessing, Feature Engineering, Model Evaluation