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A production-ready ML system that predicts task priority using behavioral and temporal features, deployed as a monitored API with drift detection and failure analysis.

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Implementation of a deep learning pipeline for Parkinson’s gait detection using video-based pose estimation and LSTM sequence modeling. Includes data preprocessing, pose extraction with Mediapipe, …

Multimodal AI system combining audio and video to detect emotional and motor decline indicators in elderly users.

AI-based classification of swallowing sounds for early dysphagia detection using deep learning and acoustic signal processing (MFCC features + neural network model).

Machine learning project for predicting rice yield using simulated remote sensing (NDVI) and meteorological data — part of Environmental AI mini projects.

Deep learning project for detecting tomato leaf diseases using TensorFlow and PlantVillage dataset. Implements Grad-CAM for explainable disease localization in smart farming.

This project aims to detect the stress level of users using data from wearable sensors. The sensors used include: - Heart Rate - Steps - Skin Temperature

This mini project implements a **Deep Q-Network (DQN)** agent to solve the classic control problem **CartPole-v1** from OpenAI Gym.

Medical AI: Pneumonia Classification (Image Classification)