Multi-modal OCR pipeline optimized for ML training (text, figure, math, tables, diagrams)
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Updated
May 13, 2026 - Python
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
O Foul_Calculator é um aplicativo que calcula automaticamente as faltas escolares em horas, com base na porcentagem de presença do aluno.
An individual data analysis project in R, focusing on the educational findings in School data & Student Improvement
Python-based Canvas API LMS Integration
Binary classifier predicting student exam outcomes using study habits, Decision Tree: 82% accuracy, Logistic Regression comparison
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.
Creating a toy-model approach for applying Quantum Principal Component Analysis for Educational Data
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.
Interactive dashboard and educational vulnerability index for Rio Grande do Sul municipalities using Python, Streamlit, geospatial analysis and Generative AI.
A Tableau data story that consists of multiple visualizations analyzing the relationship between marriage and education trends in the United States between 1995 and 2015, determining how each trend was impacted by economic recessions over the years, and investigating the relationship's overall impact on each state's median household income.
Educational data analysis to investigate patterns and factors associated with school dropout using Python, data science techniques and Machine Learning
Machine Learning aplicado à predição de risco de defasagem educacional — Datathon FIAP
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