ANJAL User

I’m a Machine Learning Developer currently working independently while pursuing my B.E. in Computer Engineering at IOE, Pokhara. I love turning messy data into reliable models, then validating and improving them through careful experimentation.

In my role as a self-directed Machine Learning Developer, I built and evaluated regression and classification models using Scikit-learn, with strong EDA and feature engineering using Pandas and NumPy. I also practice deep learning workflows in PyTorch—especially CNN-based image classification and transfer learning—so I can deliver strong results on real tasks.

My projects reflect the way I like to work: fast, collaborative, and deployment-minded. For SajiloKheti—Leaf Disease Detection, I built a ResNet50 transfer learning image classifier in PyTorch, created an inference pipeline, and served it through a FastAPI endpoint within a 60-hour hackathon.

I’ve also built a prototype for the Disaster Assistance Management System for the Imagine Cup, contributing to architecture and development using Python and React.js. Across datathons and ML competitions, I’ve strengthened my end-to-end workflow—data cleaning, EDA, feature engineering, training, validation, and submissions—because I’m genuinely curious about learning and improving every iteration.