Multi-modal OCR pipeline optimized for ML training (text, figure, math, tables, diagrams)
EdOptimize is an open-source learning analytics platform for K-12 digital learning systems.
Machine learning pipeline analyzing Open University educational data to predict student outcomes and model VLE engagement.
Datos públicos del MINEDUC para actividades docentes de analítica sobre admisión a la educación superior en Chile.
Material docente de analítica de datos educacionales con información pública del MINEDUC de Chile.
Análisis de los resultados PAES desde la Admisión 2023 en adelante identificando el ranking de los colegios.
A free, game-inspired English learning platform with structured 45-minute lessons, adaptive practice, vocabulary mini-games, and a local mentor. Proprietary freeware with an open educational data layer.
Содержит примеры цифровых логических схем к Logisim-Evolution
An individual data analysis project in R, focusing on the educational findings in School data & Student Improvement
O Foul_Calculator é um aplicativo que calcula automaticamente as faltas escolares em horas, com base na porcentagem de presença do aluno.
Python-based Canvas API LMS Integration
An advanced machine learning project for analyzing student performance, utilizing sociodemographic indicators. Hosted on AWS Elastic Beanstalk for real-time predictions and integrated with AWS CodePipeline for continuous integration and deployment.
For this project we will attempt to use K-Means Clustering to cluster Universities into to two groups, Private and Public.. The algorithm uses unsupervised learning.
Binary classifier predicting student exam outcomes using study habits, Decision Tree: 82% accuracy, Logistic Regression comparison
Creating a toy-model approach for applying Quantum Principal Component Analysis for Educational Data
Academic machine learning project predicting student academic performance for the UdeA AI4ENG Kaggle competition. Implements data cleaning and label encoding with Gradient Boosting, XGBoost, AdaBoost, and CatBoost classifiers in Jupyter Notebooks, using the Kaggle API for data download.
NUK Cathy Data Workspace
Interactive dashboard and educational vulnerability index for Rio Grande do Sul municipalities using Python, Streamlit, geospatial analysis and Generative AI.
Automated metadata extraction pipeline for International Large-Scale Assessment (ILSA) documents using RAG-based LLM architecture. 99.2% classification accuracy across 1,622 studies.
Machine Learning aplicado à predição de risco de defasagem educacional — Datathon FIAP
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