developed a comprehensive model to analyze and forecast stock market trends using Long Short-Term Memory (LSTM) neural networks
The model was trained on historical stock data to predict future price movements
Key features include data preprocessing, time series analysis, and the implementation of LSTM for effective forecasting
The project demonstrates expertise in machine learning, deep learning techniques, and financial data analysis
It also highlights my ability to work with Python libraries such as TensorFlow, Keras, and Pandas, and to visualize results with tools like Matplotlib
