MSc Data Science student at the University of Aberdeen, with extensive experience in data analysis, machine learning, and deep learning. Proven track record in leveraging advanced analytics and AI to solve complex problems and drive strategic decisions. Strong background in Industrial Economics with skills in statistical modeling, ETL processes, data visualization, and SQL. Committed to continuous learning and professional development, holding multiple IBM certifications.
Image Classification using CNNs
- Developed a CNN using TensorFlow and Keras, achieving 90% accuracy in classifying images.
- Implemented data augmentation techniques to enhance model performance.
Sentiment Analysis using RNNs
- Built an LSTM model to analyze customer reviews, achieving 88% accuracy in sentiment classification.
- Utilized text preprocessing techniques and word embeddings for better text representation.
Customer Churn Prediction
- Developed a predictive model using neural networks, achieving 85% accuracy.
- Optimized hyperparameters and performed extensive data preprocessing to improve model robustness.
Real-time Object Detection for Surveillance
- Implemented the YOLO algorithm for real-time object detection using OpenCV and TensorFlow.
- Achieved 90% accuracy in detecting objects, significantly improving surveillance system effectiveness.