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Hello!
I'm Arun Arumugam
A passionate and enthusiastic data science professional with a relentless curiosity for uncovering insights from data. I thrive on learning new techniques and applying them to real-world challenges, driven by a deep love for solving problems with data. With a strong focus on continuous growth, I am committed to mastering the latest tools and methodologies in data science. I believe in the power of data to transform ideas into impactful solutions, and I am excited to bring my energy and dedication to every project I undertake.
Projects
Exoplanet Habitability and Earthlikeness Prediction
​What if the next habitable world is just a few light-years away?
This project harnessed machine learning to evaluate the potential habitability and Earth-likeness of exoplanets, using key astronomical data. By developing a model that achieved 85% accuracy through classification and regression techniques, and optimizing it with advanced feature engineering, I contributed to the search for planets with Earth-like qualities, potentially expanding our understanding of life beyond Earth.
Potato Disease Classifier
Can artificial intelligence help farmers protect their crops from devastating diseases?
In this project, I developed a deep learning model using convolutional neural networks (CNNs) to classify potato plant diseases from images with high accuracy. Leveraging data augmentation techniques, the model was further optimized for robustness. The deployment was accomplished using Docker, Flask, and FastAPI, providing an interactive dashboard that enables real-time disease detection and actionable insights for farmers and agricultural experts.
Spider-Verse Classifier
This project involves developing a machine learning classifier to identify Spider-Man actors from the Spider-Verse series based on their images. Leveraging a custom dataset gathered through a Pinterest scraper, the classifier uses feature extraction techniques and traditional machine learning algorithms to differentiate between actors like Andrew Garfield, Tobey Maguire, and Tom Holland. The model's accuracy improves with larger datasets, showcasing its capability to adapt and refine predictions. The implementation integrates image preprocessing, feature extraction, and classification to deliver reliable results. This project exemplifies the application of machine learning in a creative context, merging pop culture with advanced data analysis techniques.
Skills
Python
NLP
Data Visualization
Numpy
SQL
Pandas
Story Telling
Scikit-Learn
Machine Learning
