Zahra Toroghi

Developed supervised machine learning models for Alzheimer's classification using Python, contributing to ongoing research in the field.

Designed and optimized NLP models using Python, NLTK, and spaCy, enhancing text classification accuracy by 20%. Developed sentiment analysis tools, improving accuracy by 25% through deep learning integration.

Enhanced model accuracy by 20% for image classification tasks through optimization of neural network architectures. Implemented data augmentation techniques, improving validation accuracy by 15%.

Created efficient data analysis pipelines, resulting in a 25% increase in processing speed. Enhanced patient readmission predictions with ML models, improving accuracy by 15%.

Reduced page load time from 3 seconds to 1.5 seconds. Designed and implemented custom plugins to increase system efficiency and capabilities.

Improved system performance by reducing processing time of key operations by 50%. Created and integrated custom APIs for data exchange within the organization.

Enhanced recommendation engine accuracy by 25% through machine learning algorithms. Increased data processing speed by 50% using distributed computing techniques.

Instructed students in error correction coding, focusing on mathematical methods and algorithms, enhancing their understanding of complex concepts.

Improved object detection model accuracy by 30% using deep learning techniques. Reduced processing time for image classification tasks by 40%.