- Machine Learning Applications: Fraud detection, water quality classification, and smart agri-fishery solutions.
- Deep Learning: Expertise in Convolutional Neural Networks (CNN) for tasks like image classification and disease detection.
- Data Processing: Handling imbalanced datasets with techniques like SMOTE, ADASYN, and SMOTE-Tomek Links.
- Algorithm Optimization: Comparing and implementing various models, including Weighted KNN, Gaussian Naive Bayes, and Artificial Neural Networks.
- Practical Deployment: Creating web-based AI solutions using Streamlit for real-world applications.
- AI in Robotics: Integration of machine learning with robotic autonomy, utilizing ROS 1 and ROS 2.
- Visualization: Developing visual tools for data insights and model performance evaluation.