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django_learning

This repository helped me learn Django

flight-delay-predction

A Kaggle dataset related to flight delays was analyzed using several tree-based models: DecisionTreeClassifier from the sklearn library, RandomForest also from sklearn, and GradientBoostingTreeDecision from the CatBoost library

gym-database-mysql

Here there's a conceptual, logical and physical model of the same database.

intro_machine-learning_classification

This Jupyter Notebook serves as a comprehensive guide to performing support vector machine (LinearSVC) classification and calculating accuracy scores for machine learning tasks. It provides step-by-step instructions and code examples for building, training, and evaluating a LinearSVC classifier

machine-learning-behind-the-curtain

This dataset was used to learn more about how some machine learning models work: KNN, Naive Bayes, and Decision Tree. It also includes some model evaluation metrics: Precision, Recall, Accuracy, and F1-Score. These metrics were derived from the confusion matrix.

rate-monotonic-scheduling

analysis addresses how to determine whether a group of tasks, whose individual CPU utilization is known, will meet their deadlines.

school-database-mysql

titanic

Using knn in the titanic dataset