gridsearch

A Reproducible Workflow for Structural and Functional Connectome Ensemble Learning

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.

Aims at attributing the big-five personality traits to authors of essays by analyzing their works.

Cross Validation, Grid Search and Random Search for TensorFlow 2 Datasets

A lightweight tool to manage and track your large scale machine leaning experiments

dataclasses enhanced with type validation and serialization

Propositional structure recovery and truth table entropy for hyperparameter search space pruning. Two papers, one library.

Combine grid search with early stopping via cross validation

Prediction of forest cover type in Python.

A set of functions to optimize machine learning models

Backpropagation and automatic differentiation, and grid search from scratch.

Applications/Files created in my internship at the Institute for Artificial Intelligence in Bremen (http://ai.uni-bremen.de/).

ML model optimization algorithms such as random search, grid search, and Bayesian optimization. are illlustrated with codes.

Fast C/Python Backtesting Framework with Multi-Parameter Grid Search & Visualizations

Self-assigned project for visual analytics class at Aarhus University, 2021

Reducción de tiempo de ejecución de los algoritmos de Machine Learning con búsqueda de parámetros en GridSearch.

Breast Cancer Wisconsin Dataset Classifier with Scikit-learn and Streamlit

Testing several hyperparameter optimization techniques.

Deep Q Learning (DQN) neural net to optimize a lunar lander control policy using OpenAI Gym environment.

A simple python interface for running multiple parallel instances of a python program (e.g. gridsearch).