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#
elliptic-envelope
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[Competition] KAMP : 2022년 제2회 K-인공지능 제조데이터 분석 경진대회 : 시계열 분석 기반 용해물 품질 예측 AI 모델 개발
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__CourseWork__
ml course-work roc-curve gradient-boosting-classifier local-outlier-factor isolation-forest oneclasssvm elliptic-envelope
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Repository for the microassignments and final project of the UC3M's MSc in Connected Industry 4.0's Intelligent Processing Data Tools subject
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An example of improving data quality and identifying anomalies within a real-life dataset for master data management or data engineering.
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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
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This repository hosts a comprehensive, web-based Anomaly Detection platform designed to identify irregularities across three distinct domains: Network Security, Industrial Manufacturing, and Medical Imaging. Built with Flask REST API and powered by PyTorch and Scikit-learn.
computer-vision logistic-regression flask-api machine-learning-models isolation-forest pytorch-cnn one-class-svm anomal elliptic-envelope
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