This finance project aimed to use data science and machine learning techniques to analyze and predict stock prices. We collected data using Yahoo Finance API and then transformed and engineered features to improve our model's performance.
We used various machine learning algorithms such as Linear Regression, Random Forest, K-Nearest Neighbors, Gradient Boosting Regressor, and Support Vector Regressor to predict future stock prices.
Furthermore, we also utilized technical indicators such as moving averages, Relative Strength Index (RSI), and Bollinger Bands, to gain a deeper understanding of the stock's behaviour and provide more insights into our predictions.
Overall, this project demonstrated the power of data science and machine learning in finance and the potential for predicting future stock prices accurately.