ML course exercises for MSc AI — covering regression, classification, time series, NLP, deep learning, and clustering using scikit-learn, Pandas and TensorFlow in Python and Jupyter Notebooks.

Clinical heart disease prediction system (MSc AI, BSBI). Uses supervised ML on patient vitals with a full diagnostic pipeline: normalization, feature analysis, and high-precision classification models for early-stage medical decision support.

A predictive analytics project developed during my MSc AI at BSBI. This project implements a binary classification pipeline to predict customer purchase behavior based on demographic and interaction data. It covers the full ML lifecycle: from Exploratory Data Analysis (EDA) and feature engineering to model selection and performance benchmarking.

List of ideas that can be applied to a Masters in AI research paper

A quantitative research & analytics project developed during my MSc AI at BSBI. It focuses on evaluating NLU performance and user interaction patterns through data-driven insights. The project utilizes Python and advanced data visualization to identify intent classification gaps and provide systematic optimization strategies for conversational AI.

A Multimodal AI assistant for automated plant pathology diagnosis, featuring an interactive UI built with Gradio. Developed during my MSc AI at BSBI, the system utilizes a fine-tuned EfficientNet-B0 architecture for high-accuracy image classification, integrated with natural language processing to provide real-time disease identification.