As a recent graduate with a strong foundation in machine learning and data science, I am eager to leverage my academic knowledge and hands-on experience to contribute to innovative projects and impactful data solutions as a Data Scientist. My background includes designing and implementing data-driven solutions for various business challenges, with expertise in predictive modeling, artificial intelligence, machine learning, and big data technologies. I bring strong analytical thinking, problem-solving skills, and the ability to translate complex data into actionable insights, aiming to enhance efficiency and effectiveness within a dynamic team.
Languages and Libraries:
Framework and Computer skills:
Soft Skills:
Automatic License Plate Recognition for Smart Home Garage, May 2024 - Sept 2024
· Researched Optical Character Recognition (OCR) and Object Detection techniques for Automatic License Plate Recognition
· Optimized the garage door opening process of a smart home through the deployment of ALPR models onto microcontrollers.
· Conducted research into state-of-the-art techniques such as transfer learning to fine-tune deep learning models for object detection and classification.
Machine Health Monitoring with Machine Learning, Sept 2022 - Dec 2022
· Utilized machine learning techniques to create models that effectively analyze motor performance and anticipate potential failure using vibration information
· Strengthened research and development abilities by extensively researching and testing, resulting in the identification of the optimal model architecture
· Conducted hyperparameter tuning to enhance model performance.
Hyper Parameter Research for Tissue Patch Clustering, Sept 2023 - Dec 2024
· Analyzed and identified the best approach for classifying tissue patch images through research on model selection and hyperparameter tuning
· Conducted parametric experiments with diverse unsupervised clustering models and hyperparameters
· Evaluated model performance by creating metric plots for accuracy, precision, recall, F1 score and AUC.