Repo that relates to the Medium blog 'Using Bayesian Optimization to reduce the time spent on hyperparameter tuning'
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Updated
Mar 26, 2019 - Jupyter Notebook
Repo that relates to the Medium blog 'Using Bayesian Optimization to reduce the time spent on hyperparameter tuning'
This repository contains Local Search Algorithms implemented on Magic Square problem.
A hyperopt wrapper - simplifying hyperparameter tuning with Scikit-learn style estimators.
Hyperparameter-Optimization-Tutorial
All Machine Learning Templates (Seaborn,K fold, Grid Search, Random Search,AUC-ROC for all major algorithms)
Predictions on NHANES3 dataset, predicting mortality
Machine Learning aplicado al mantenimiento predictivo. Se realizaron 2 modelos: 1 por medio de clasificación binaria que predice si una máquina fresadora estará en riesgo de fallar o no, y el 2 modelo a través de clasificación multiclase que predecirá el modo de falla
ML model optimization algorithms such as random search, grid search, and Bayesian optimization. are illlustrated with codes.
Implementation of Hyper-parameter tuning of ML models
Random search command line driver to optimize a parameter surface determined by a command
HackerEarth Machine Learning challenge: Adopt a buddy
Testing several hyperparameter optimization techniques.
This repository demonstrates an investigation of listing price indicator of Airbnb
Implementação de três métodos de busca de elementos
Try to Implement different Envirnment and RL algorithms
Técnica de validação cruzada estratificada e seleção de hiperparâmetros com Randon Search.
meta-heuristic search algorithms
AI-CyberSec 2021 Workshop CEUR Publication(AI-2021 Forty-first SGAI International Conference)
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