B.Sc,Data Science Graduate
Hi, I’m Dhanush, a Data Science graduate with a strong foundation in Python, SQL, Excel, Power BI, Tableau, and machine learning. I’ve applied my skills across various projects, including credit card fraud detection, crop yield prediction, sentiment analysis, and classification models. I’ve built and deployed machine learning models, performed data cleaning, visualization, and developed end-to-end solutions that turn data into actionable insights. I’m passionate about solving real-world problems through data and continuously expanding my knowledge in analytics and AI.
I completed an internship as a Data Analyst at Ozibook, a Bangalore-based startup, where I was responsible for lead generation and data-driven decision-making. My work involved utilizing tools like Apollo and ContactOut to support business growth through strategic data insights and creating dashboards to provide dynamic interaction.
RVS College of Arts and Science
Coimbatore , Sulur
GPA 8.9
Kathiravan Matric Higher secondary School
Percentage 85%
> 🌾 Predicts agricultural crop production based on historical state, district, crop, and seasonal data. 📊 Trained on a 3.4 lakh+ record dataset, using Random Forest with high R² scores (>0.97). 🌱 Helps farmers and planners estimate yields for future seasons. 🖥️ Streamlit-powered app allows single-input forecasting by region and season. 🔧 Real-world utility in agri-tech and government planning dashboards.
Live Demo> 📺 Fetches and analyzes real-time YouTube comments using the YouTube Data API. 🧠 Uses TextBlob NLP to classify public sentiment as Positive, Negative, or Neutral. 🎯 Highlights top buzzwords and emotion trends from videos. 💬 Great for creators, marketers, or analysts tracking audience reaction. 🖥️ Users just paste the video URL and get live sentiment breakdown.
Live DemoI'm building an interactive portfolio website that combines data, design, and storytelling. The site showcases my projects, skills, and learning journey, while I explore front-end development and experiment with animations using Blender and Adobe Animate. The goal is to create a digital space that reflects both my technical expertise and creative growth.
Viewing Right Now🚨 A machine learning app to detect fraudulent transactions using Random Forest and XGBoost. 💡 Built with real-world transaction data, achieving over 97% accuracy. 🔍 Includes data preprocessing, EDA, and model tuning. 🖥️ Users can test with CSV files or manually input transaction details. 🚀 Deployed with an intuitive Streamlit interface for real-time predictions.
Live Demo