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Aplicando e praticando diferentes modelos de machine learning na sua empresa, utilizando algoritmos de classificação, comparando o resultado de algoritmos lineares e não lineares, empregando Support Vector Machines, Árvores de Decisão e Dummy Classifier.
This project uses ensemble method models of decision trees, voting classifier, support vector machines, adaboost, logistic regression, dummy classifier, and bagging classifier to predict malignant or benign cells for breast cancer.
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Applied SVC classifier and Logistic Regression classifier algorithm onto credit card transaction dataset to detect any fraud.
This project explores the predictive modeling workflow using the Kaggle competition "Titanic - Machine Learning from Disaster." It emphasizes key stages like data analysis and model evaluation, aiming to identify the optimal model. Through a real-world approach, we enhance our understanding of the workflow and emphasize rigorous model evaluation.