Saka Kishore babu

I built an obesity classification model using dietary habits and physical activity data, deliberately excluding BMI. LightGBM outperformed the other models I benchmarked, achieving approximately 90% accuracy, and I deployed the final model as a Streamlit app for real-time predictions.

For my heart disease prediction project, I developed neural network and random forest models using patient health data. I cleaned and prepared the data, then evaluated the models with metrics including Accuracy, Precision, Recall, F1 Score, and ROC-AUC.

I also built a Li-Fi communication prototype with two Arduino boards. Its transmitter sent data through LED light modulation, while an IR sensor-based receiver detected, decoded, and displayed the message.

During my AI-ML-DS Virtual Internship at IIDT BlackBucks (under APSCHE), I worked with real-world datasets and applied data preprocessing, model building, and evaluation. I’m an Electronics and Communication Engineering student at SRKR Engineering College looking for an entry-level role where I can apply and grow my software development and embedded systems skills.