Anomaly Detection in Time Series Data with Keras

Design and train an LSTM autoencoder using the Keras API with Tensorflow 2 as the backend to detect anomalies (sudden price changes) in the S&P 500 index.

• Project Overview and Import Libraries
• Load and Inspect the S&P 500 Index Data
• Data Preprocessing
• Temporalize Data and Create Training and Test Splits
• Build an LSTM Autoencoder
• Train the Autoencoder
• Plot Metrics and Evaluate the Model
• Detect Anomalies in the S&P 500 Index Data