Artificial Intelligence graduate from Yarmouk University with hands-on experience in deep learning, machine learning, and AI agent development. Developed a deep learning model using PubMedBERT for predicting drug side effects, showcasing strong technical skills in Python and natural language processing. Seeking to leverage expertise in AI and data analysis to contribute to innovative projects in a dynamic organization.
Developed a deep learning approach for predicting drug side effects using the PubMedBERT model. This project involved preprocessing drug-related text through techniques such as text cleaning and tokenization, followed by training the model to classify and predict possible side effects. Evaluated using Accuracy, Precision, Recall, and F1-score, the model demonstrated strong performance, highlighting the effectiveness of transformer-based models in healthcare applications.
Completed several courses focusing on artificial intelligence, deep learning, and machine learning, enhancing technical skills and practical knowledge in the field.