Sequential model-based optimization with a `scipy.optimize` interface

Example code for paper "Bilevel Optimization: Nonasymptotic Analysis and Faster Algorithms"

PyTorch implementation of Proximal Gradient Algorithms a la Parikh and Boyd (2014). Useful for Auto-Sizing (Murray and Chiang 2015, Murray et al. 2019).

Flexible Bayesian Optimization in R

A small library for managing deep learning models, hyperparameters and datasets

Tools for Optuna, MLflow and the integration of both.

Hyperparameters-Optimization

Example Code for paper "Provably Faster Algorithms for Bilevel Optimization"

Hyperparameter optimisation utility for lightgbm and xgboost using hyperopt.

A dl management front end

Some experiments to empirically analyze how the parameters of LWE impact the correctness of the algorithm on a single bit.

Deep Learning Specialization. Master Deep Learning, and Break into AI

Hyper-Parameter Analyzer

This repository Consist of Course Material, Assignment And Quizes Attempted in Specialization Course by Coursera

Study projects developed during data science courses

Interactive exploration of hyperparameter tuning results with ipywidget and plotly in jupyter notebook.

"oxayavongsa/projects" is a public GitHub repository serving as a diverse AI/ML Project Portfolio. Using Python coding and Juptyer notebook for multiple methodologies to model statistical algorithms.

Automatically create a config of hyper-parameters from global variables

Assignment titled "A Brief Review of Hyperparameter Optimization Methods for Machine Learning" for Research Methods in Computer Science course at Ryerson University

Distributed Asynchronous Hyperparameter Optimization in Python