ST. MARK ADEBAYO

Engineered a multi-modal RAG system, seamlessly integrating text, images, and documents to significantly expand knowledge retrieval capabilities.

Leveraged DistilBERT for generating robust embeddings, enhancing the system's ability to process and understand diverse data types.

Implemented ElasticSearch for efficient information retrieval, enabling the chatbot to deliver accurate and contextually relevant responses across NLP and visual queries.

Designed and implemented a machine learning model for accurate Lagos apartment price prediction, optimizing performance through comprehensive data preprocessing, feature engineering, and model tuning.

Built and deployed a user-friendly Streamlit web application, enabling users to input property details and receive instant price predictions, enhancing accessibility.

Leveraged ElasticNet for the core predictive model and applied clustering techniques to effectively categorize property titles and locations, improving model robustness.

Developed a machine learning model to accurately analyze plant health based on image input, facilitating early detection of diseases.

Incorporated deep learning techniques using Convolutional Neural Networks (CNNs) to effectively detect and classify plant diseases.

Generated actionable care recommendations, improving plant health management and promoting healthier plant growth.

Engineered an image classification system to accurately identify and categorize sports celebrities, demonstrating strong computer vision capabilities.

Fine-tuned a pre-trained ResNet model, achieving high accuracy on a custom dataset for robust celebrity classification.

Applied convolutional neural networks (CNNs) to build an efficient and scalable image recognition solution.