"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.

Flexible Bayesian Optimization in R

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

Automatically create a config of hyper-parameters from global variables

Study projects developed during data science courses

Hyper-Parameter Analyzer

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

A dl management front end

Tools for Optuna, MLflow and the integration of both.

Hyperparameters-Optimization

Hyper-parameter tuner (for computer vision and reinforcement learning)

Project-Based Intern from Home Credit Indonesia, Credit Risk Classification based on bad/good credit

Experiment with different optimizer, layers, filters, regularization for Y-Net(CNN) with CIFAR 10 and CIFAR 100 dataset

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

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

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

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

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

Hyperparameter optimisation utility for lightgbm and xgboost using hyperopt.

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