This project builds a complete Machine Learning & Deep Learning pipeline to estimate the State of Health (SOH) of Li-ion batteries using the NASA Battery Dataset.
The pipeline starts from raw cycle data and ends with highly accurate deep learning models suitable for real-world Battery Management Systems (BMS) and embedded deployment (e.g., ESP32)