🔭 Currently Working On
Building scalable data pipelines with PySpark, Hadoop & distributed systems
Designing high-performance ML models for real-world datasets (99%+ accuracy)
End-to-end data-driven systems: ingestion → processing → modeling → visualization
👯 Open to Collaborate On
Large-scale Machine Learning & Data Engineering projects
Open-source contributions in AI/ML, Distributed Systems, Data Platforms
Real-world applications involving high-volume data & system scalability
🤝 Seeking Help With
Production-grade ML deployment (MLOps) & model monitoring
System design for scalable AI systems
Breaking into top-tier tech roles (DS/ML/DE roles)
🌱 Currently Learning
Advanced System Design for Data & ML Systems
Distributed Computing (Spark internals, optimization techniques)
Cloud (AWS/GCP) for scalable ML pipelines
Advanced DSA & problem-solving for top tech interviews
💬 Ask Me About
Designing end-to-end ML pipelines
Optimizing large-scale data processing (PySpark, SQL)
Model evaluation, feature engineering & performance tuning
Data visualization & storytelling (Power BI, analytics dashboards)
⚡ Fun Fact
Built ML models with 99.45% accuracy & reduced processing time by 60%
I enjoy solving problems where data meets scalability
📊 Highlight Projects
Traffic Flow Prediction (PySpark + ML)
→ 99.45% accuracy | 60% faster processing
OTT Analytics Dashboard (Power BI)
→ Improved decision-making by 20%
Facial Attendance System (OpenCV)
→ 95% accuracy | 40% latency reduction
