__CourseWork__

Repository for the microassignments and final project of the UC3M's MSc in Connected Industry 4.0's Intelligent Processing Data Tools subject

[Competition] KAMP : 2022년 제2회 K-인공지능 제조데이터 분석 경진대회 : 시계열 분석 기반 용해물 품질 예측 AI 모델 개발

At Infosys Springboard, I worked on a project focused on unsupervised anomaly detection in healthcare providers. I implemented three machine learning algorithms—Isolation Forest, Elliptic Envelope, and One-Class SVM—as well as a deep learning approach using autoencoders. Additionally, I conducted individual SHAP analysis

An example of improving data quality and identifying anomalies within a real-life dataset for master data management or data engineering.