Welcome to my GitHub profile! I'm an Artificial Intelligence and Data Science student passionate about building practical projects using Python, Machine Learning, Deep Learning, Computer Vision, Data Analytics, and Web Technologies.
I enjoy learning new technologies, solving real-world problems, and turning ideas into working applications.
- 🎓 B.Tech student in Artificial Intelligence & Data Science
- 🐍 Passionate about Python
- 🤖 Interested in Artificial Intelligence and Machine Learning
- 🧠 Building Deep Learning and Computer Vision projects
- 📊 Interested in Data Science and Data Analytics
- 🌐 Learning Full Stack Development
- 💻 Building practical projects for my portfolio
- 📚 Continuously improving my technical skills
- 🎯 Goal: Become a skilled AI & Data Science professional
- Machine Learning
- Deep Learning
- Convolutional Neural Networks
- Computer Vision
- Image Classification
- Data Preprocessing
- Model Evaluation
- Exploratory Data Analysis
- Data Cleaning
- Data Visualization
- Exploratory Data Analysis
- Statistical Analysis
- Predictive Modeling
- Microsoft Excel
A CNN-based Deep Learning application that classifies waste images into Organic and Recyclable categories.
Technologies: Python, TensorFlow, Keras, CNN, Computer Vision, Streamlit
Test Accuracy: 89.53%
A personal finance management and analytics application with transaction tracking, expense analysis, budget planning, goals, alerts, and prediction features.
Technologies: Python, Streamlit, SQLite, Pandas, Plotly, Scikit-learn
A web application for tracking daily water consumption, goals, progress, reminders, and daily streaks.
Technologies: HTML, CSS, JavaScript, Node.js, Express, JSON Server
A full-stack web application designed to manage NGO operations including donations, volunteers, beneficiaries, events, and user authentication.
Technologies: HTML, CSS, JavaScript, Node.js, Express, MongoDB, Mongoose
A Machine Learning project that compares multiple classification algorithms for predicting heart disease.
Models Used:
- Logistic Regression
- Decision Tree
- Random Forest
Best Accuracy: 88.52%
Technologies: Python, Pandas, Scikit-learn, Matplotlib
- 🤖 Advanced Deep Learning
- 👁️ Computer Vision
- 🧠 Transfer Learning
- 📊 Advanced Data Analytics
- ✨ Generative AI
- 🚀 AI Application Deployment
- ☁️ Cloud Technologies
- ✅ Build multiple Deep Learning projects
- ✅ Strengthen Machine Learning fundamentals
- 🚀 Learn Transfer Learning
- 🚀 Learn advanced Computer Vision
- 🚀 Explore Generative AI
- 🚀 Improve Data Analytics skills
- 🚀 Build production-ready AI applications
- 🚀 Deploy projects online
- 🚀 Contribute to Open Source
- 🚀 Build a strong AI & Data Science portfolio
"Build. Learn. Improve. Repeat."
Thanks for visiting my GitHub profile.
Feel free to explore my repositories and projects.