[CORE_DIRECTIVE]
BIO
I am an Electrical & Electronics Engineer and a self-taught programmer who learns by building, breaking, and rebuilding systems. My work is driven by curiosity—when something genuinely interests me, I dive deep through hands-on coding and experimentation. I focus on AI/ML, Python programming, and research-oriented problem solving, turning ideas into working, testable solutions.
CERTIFICATIONS
PROJECTS
NERV-Neural Experiments & Real-world Validation
A full-stack AI project that integrates TensorFlow-based inference with a Django backend and a custom JavaScript interface.
NERV focuses on taking trained machine learning models and deploying them into a usable, end-to-end workflow rather than treating them as isolated experiments.
PROJECT: AM I COOKED ?
A Scikit-Learn powered web application built with a Flask backend that predicts 10-year Coronary Heart Disease (CHD) risk based on lifestyle and health indicators.
The model is trained on structured medical data and achieves ~96% accuracy, translating clinical risk factors into an easy-to-understand prediction.
MORE OPEN SOURCE PROJECTS
REPOSITORY
TENSORFLOW
A personal deep learning sandbox documenting real TensorFlow projects, from data preprocessing to model training.
REPOSITORY
OPENCV
A modular OpenCV repository progressing from image fundamentals to deep learning–based pose estimation.
REPOSITORY
MACHINE LEARNING
Beginner-friendly projects covering supervised, unsupervised, and reinforcement learning with clear explanations and code.
REPOSITORY
NEURAL NETWORK
Projects covering neural networks, CNNs, RNNs, training dynamics, and model evaluation.
[Follow Me]GitHub
PROTOCOL: LN-01LinkedIn
PROTOCOL: TX-03X / Twitter
PROTOCOL: YT-02YouTube