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1. eeg-signal-classification-using-classical-ml eeg-signal-classification-using-classical-ml Public

   EEG-based brain signal classification using classical machine learning with feature engineering and comparative model evaluation for BCI and NeuroAI research.

   Python

2. explainable-ai-medical-ml-shap-lime explainable-ai-medical-ml-shap-lime Public

   End-to-end explainable AI pipeline for medical classification using Random Forest and XGBoost with SHAP and LIME for global and local interpretability. Designed for transparent, trustworthy machine…

   Python

3. feature-engineering-and-model-selection-pipeline feature-engineering-and-model-selection-pipeline Public

   End-to-end feature engineering and classical machine learning pipeline for real-world tabular data, including preprocessing, feature selection, and scientific model selection with cross-validation.

   Python

4. multiagent-warehouse-navigation-dqn multiagent-warehouse-navigation-dqn Public

   Research-grade Reinforcement Learning framework for single-agent and multi-agent warehouse navigation using Deep Q-Networks (DQN), PyTorch, replay buffer, target networks, logging, and full test su…

   Python

5. reinforcement-learning-for-robot-navigation reinforcement-learning-for-robot-navigation Public

   Research-grade reinforcement learning framework for robot navigation, covering discrete, obstacle-aware, continuous-control, and multi-agent environments with PPO and DQN, full evaluation pipeline,…

   Python

6. unsupervised-anomaly-detection-ml unsupervised-anomaly-detection-ml Public

   Research-level implementation of unsupervised anomaly detection using KMeans, DBSCAN, Isolation Forest, and deep Autoencoders. Applied to IoT sensors, financial fraud, network intrusion, and time-s…

   Jupyter Notebook