This project utilizes Long Short-Term Memory (LSTM) neural networks to predict and forecast stock prices of a selected company (e.g., Tesla - TSLA) based on historical data. It aims to provide insights into potential future trends in stock prices, aiding investors and financial analysts in decision-making.
Components: Data Acquisition and Exploration: Fetches historical stock data from Yahoo Finance and displays an overview of the data.
Data Visualization: Generates visualizations of stock prices over time and plots training/testing sets.
Data Preprocessing: Splits data into training/testing sets and scales it using MinMaxScaler.
Model Building: Constructs and trains LSTM neural network model using Keras.
Model Evaluation and Predictions: Evaluates model performance, makes predictions on testing data, and compares them with actual prices.
Forecasting: Allows users to select a time period for future forecasting, generates forecasts using LSTM model, and displays them graphically.