Machine Learning & AI
From autonomous research agents to real-time voice assistants and medical imaging systems, these projects push the boundaries of what intelligent software can achieve.
Explore ProjectsWhat is ML & AI?
Machine Learning is a branch of artificial intelligence that enables systems to learn patterns from data and make decisions without explicit programming. From recommendation engines to autonomous vehicles, ML powers the technology that defines the modern era.
These projects demonstrate end-to-end ML workflows: data collection and preprocessing, model architecture design, training and evaluation, and production deployment with monitoring and observability.
Models Trained
Multi-architecture pipelines with CNN, VGG, YOLO, and transformer models
Real-Time Systems
Sub-2-second latency voice assistants handling 100+ concurrent sessions
Domain Coverage
Medical imaging, environmental science, autonomous research, and education
Featured Projects
AgenticAI
Autonomous multi-agent research system that generates comprehensive reports with citations in under 2 minutes.
Intelligent Codebase Review
AI-powered architectural analysis, bug detection, and automated refactoring suggestions for large repositories.
Ask My Doc
Production RAG system for natural language Q&A over documents with source citations and page references.
Voice Assistant
Real-time voice-to-voice AI system with <2s latency, handling 100+ concurrent sessions via async WebSocket streaming.
Brain Tumor Detection System
Deep learning system achieving 93% accuracy on 19K+ MRI scans using multi-model ensemble (CNN, VGG16, YOLOv8).
Local Memory AI
Privacy-first conversational AI with persistent memory, semantic search, and zero cloud dependency — runs entirely on local hardware.
Prediction System
End-to-end ML prediction pipeline with automated feature engineering, model selection, and hyperparameter tuning.
Medical Insurance Claim Predictor
ML system predicting insurance claim amounts and identifying key cost drivers using regression models and feature analysis.
AQI Prediction
Time-series ML system forecasting Air Quality Index using LSTM, Random Forest, and XGBoost with multi-pollutant analysis.
Key Capabilities
Deep Learning
Build and train neural networks for complex pattern recognition, image classification, and sequence modeling tasks.
Computer Vision
Detect, classify, and segment objects in images and video using state-of-the-art CNN and transformer architectures.
NLP & LLMs
Harness large language models for text generation, sentiment analysis, summarization, and conversational AI systems.
MLOps & Deployment
Productionize ML models with CI/CD pipelines, containerization, monitoring, and scalable serving infrastructure.
Data Engineering
Design robust data pipelines that ingest, transform, and deliver clean datasets for training and inference.
Predictive Analytics
Forecast trends, classify outcomes, and quantify risk using supervised and unsupervised learning algorithms.
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