Projeto de previsão de fraudes em instalações de aplicativos utilizando (após uma análise exploratória dos dados) diversos algoritmos de machine learning para classificação
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Jun 29, 2021 - Jupyter Notebook
Projeto de previsão de fraudes em instalações de aplicativos utilizando (após uma análise exploratória dos dados) diversos algoritmos de machine learning para classificação
Deep Q Learning (DQN) neural net to optimize a lunar lander control policy using OpenAI Gym environment.
PUBG player data (4.5million+) processed using Pandas, NumPy in Python for preprocessing, and CatBoost for match predictions. Achieved RMSE 0.08, R² close to 1, optimizing gameplay metrics.
Predict the outcome of shelter animals
Reducción de tiempo de ejecución de los algoritmos de Machine Learning con búsqueda de parámetros en GridSearch.
Self-assigned project for visual analytics class at Aarhus University, 2021
Prediction of summary source in Python.
Pattern Recognition, NYCU. Homework 4
Second project about Classification
Cat vs. Dog classification model using traditional ML methods, including data collection, splitting, HOG feature extraction, model training (e.g., SVM, Decision Tree), and fine-tuning via Grid Search.
Comparison of Models using NASA Kepler data
The aim of the project is to determine if a customer will default payment next month or not.
Various small projects covering a wide range of topics
ECE NTUA Neural Networks
A summative coursework for CSC8635 Machine Learning with Project
Implémentation des algorithmes simples de Data Science
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