Projeto de previsão de fraudes em instalações de aplicativos utilizando (após uma análise exploratória dos dados) diversos algoritmos de machine learning para classificação
-
Updated
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.
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.
Self-assigned project for visual analytics class at Aarhus University, 2021
Prediction of summary source in Python.
Pattern Recognition, NYCU. Homework 4
Datasets to build classification and regression models optimized via random search and grid search algorithms.
This project aims to predict customer churn using machine learning techniques. By understanding the factors that contribute to churn, businesses can take proactive measures to retain customers and maximize their customer base. The project focuses on developing a predictive model using machine learning algorithms to forecast customer churn.
Logistic Regression and Decision Tree models to predict Customers purchasing a Loan from the bank.
Various small projects covering a wide range of topics
Add a description, image, and links to the gridsearch topic page so that developers can more easily learn about it.
To associate your repository with the gridsearch topic, visit your repo's landing page and select "manage topics."