Passionate about building intelligent systems that solve real-world problems

I'm a Machine Learning Engineer and Full-Stack Developer who loves the intersection of AI and software engineering. My journey spans from developing healthcare analytics models to creating production-ready AI applications that make a tangible impact.

• Advanced ML algorithms and neural architectures
• Time-series forecasting with Transformers and LSTM networks
• Production ML deployment with Docker, Kubernetes, and cloud services
• MLOps best practices and CI/CD for ML systems

• 🤖 Machine Learning & Deep Learning projects
• 📊 Data-driven dashboards and visualization tools
• 🌐 Full-stack applications with AI integration
• 📈 Time-series forecasting and predictive analytics
• 🔬 Open-source AI/ML tools

An intelligent interview preparation system powered by AI that provides real-time feedback and personalized coaching.

Features:

• 🤖 AI-powered question generation based on job roles
• 🎯 Real-time feedback on answers and body language
• 📈 Performance analytics and improvement tracking
• 💬 Natural language processing for answer evaluation

Tech Stack: Python NLP TensorFlow FastAPI React

An interactive web-based platform for visualizing sorting and pathfinding algorithms in real-time. Built with React and modern web technologies.

Features:

• 🔄 Real-time visualization of sorting algorithms (Bubble, Quick, Merge, Heap, Insertion)
• 🗺️ Interactive pathfinding with Dijkstra's, A*, BFS, and DFS algorithms
• 🎨 Customizable grid with obstacles and weighted nodes
• ⚡ Adjustable animation speed and array size controls
• 📊 Step-by-step algorithm execution with visual feedback

Tech Stack: React JavaScript CSS3 Algorithm Visualization

A comprehensive time-series forecasting system for predicting energy consumption patterns with interactive visualizations.

Features:

• 📊 Advanced time-series models (LSTM, Prophet, ARIMA)
• 📈 Interactive dashboards with Plotly/Dash
• 🔮 Multi-step ahead forecasting
• 📉 Anomaly detection and trend analysis

Tech Stack: Python PyTorch Plotly Streamlit Pandas

Machine learning models for healthcare data analysis, providing insights for better patient outcomes and resource optimization.

Features:

• 🧠 Predictive models for patient risk assessment
• 📊 Data visualization for clinical insights
• 🔍 Feature importance analysis
• 📈 Performance metrics tracking

Tech Stack: Python scikit-learn Pandas Matplotlib

🧠 Machine Learning
🍵 Java development
⚛️ React & Frontend
🐍 Python Development
📈 Time-Series Models
🌐 Full-Stack Dev
🤗 Hugging Face Transformers (Whisper, RoBERTa)

• 🎙️ Whisper - Worked with OpenAI's automatic speech recognition model for transcription and audio processing tasks
• 📝 RoBERTa - Implemented and fine-tuned RoBERTa models for NLP tasks including text classification and sentiment analysis
• 🤗 Hugging Face Ecosystem - Extensive experience with transformer models, tokenizers, and the Transformers library

I'm always open to interesting conversations and collaboration opportunities. Whether you want to discuss ML models, brainstorm on a project, or just chat about tech, feel free to reach out!