Cross Validation, Grid Search and Random Search for TensorFlow 2 Datasets
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Updated
May 20, 2024 - Python
Cross Validation, Grid Search and Random Search for TensorFlow 2 Datasets
Combine grid search with early stopping via cross validation
Breast Cancer Wisconsin Dataset Classifier with Scikit-learn and Streamlit
A Reproducible Workflow for Structural and Functional Connectome Ensemble Learning
Backpropagation and automatic differentiation, and grid search from scratch.
hgboost is a python package for hyper-parameter optimization for xgboost, catboost or lightboost using cross-validation, and evaluating the results on an independent validation set. hgboost can be applied for classification and regression tasks.
Prediction of molecule type in Python.
Using supervised learning on Lending Club loan data to predict default and / or bad loans
Sklearn compatible gridsearch based on a validation set.
Classification of bird images in Python.
Deep Q Learning (DQN) neural net to optimize a lunar lander control policy using OpenAI Gym environment.
Pattern Recognition, NYCU. Homework 4
A lightweight tool to manage and track your large scale machine leaning experiments
Prediction of summary source in Python.
Prediction of forest cover type in Python.
Self-assigned project for visual analytics class at Aarhus University, 2021
A simple python interface for running multiple parallel instances of a python program (e.g. gridsearch).
Reducción de tiempo de ejecución de los algoritmos de Machine Learning con búsqueda de parámetros en GridSearch.
Testing several hyperparameter optimization techniques.
Applications/Files created in my internship at the Institute for Artificial Intelligence in Bremen (http://ai.uni-bremen.de/).
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