12 Repositories
Python hyperparameters Libraries
Python code for the paper How to scale hyperparameters for quickshift image segmentation
How to scale hyperparameters for quickshift image segmentation Python code for the paper How to scale hyperparameters for quickshift image segmentatio
0 Jan 25, 2022
Hyperparameters tuning and features selection are two common steps in every machine learning pipeline.
shap-hypetune A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models. Overview Hyperparameters t
422 Jan 8, 2023
Keepsake is a Python library that uploads files and metadata (like hyperparameters) to Amazon S3 or Google Cloud Storage
Keepsake Version control for machine learning. Keepsake is a Python library that uploads files and metadata (like hyperparameters) to Amazon S3 or Goo
1.6k Dec 29, 2022
Open-source implementation of Google Vizier for hyper parameters tuning
Advisor Introduction Advisor is the hyper parameters tuning system for black box optimization. It is the open-source implementation of Google Vizier w
1.5k Jan 4, 2023
Hyperopt for solving CIFAR-100 with a convolutional neural network (CNN) built with Keras and TensorFlow, GPU backend
Hyperopt for solving CIFAR-100 with a convolutional neural network (CNN) built with Keras and TensorFlow, GPU backend This project acts as both a tuto
103 Jul 22, 2022
scikit-learn models hyperparameters tuning and feature selection, using evolutionary algorithms.
Sklearn-genetic-opt scikit-learn models hyperparameters tuning and feature selection, using evolutionary algorithms. This is meant to be an alternativ
180 Dec 20, 2022
Code and hyperparameters for the paper "Generative Adversarial Networks"
Generative Adversarial Networks This repository contains the code and hyperparameters for the paper: "Generative Adversarial Networks." Ian J. Goodfel
3.5k Jan 8, 2023
Code base for the paper "Scalable One-Pass Optimisation of High-Dimensional Weight-Update Hyperparameters by Implicit Differentiation"
This repository contains code for the paper Scalable One-Pass Optimisation of High-Dimensional Weight-Update Hyperparameters by Implicit Differentiati
8 Aug 28, 2022
easyopt is a super simple yet super powerful optuna-based Hyperparameters Optimization Framework that requires no coding.
easyopt is a super simple yet super powerful optuna-based Hyperparameters Optimization Framework that requires no coding.
9 Feb 4, 2022
Official Pytorch implementation of paper "Reverse Engineering of Generative Models: Inferring Model Hyperparameters from Generated Images"
Reverse_Engineering_GMs Official Pytorch implementation of paper "Reverse Engineering of Generative Models: Inferring Model Hyperparameters from Gener
100 Dec 18, 2022
Ever felt tired after preprocessing the dataset, and not wanting to write any code further to train your model? Ever encountered a situation where you wanted to record the hyperparameters of the trained model and able to retrieve it afterward? Models Playground is here to help you do that. Models playground allows you to train your models right from the browser.
Models Playground 🗂️ Upload a Preprocessed Dataset 🌠 Choose whether to perform Classification or Regression 🦹 Enter the Dependent Variable ?
19 Dec 10, 2022
A Sklearn-like Framework for Hyperparameter Tuning and AutoML in Deep Learning projects. Finally have the right abstractions and design patterns to properly do AutoML. Let your pipeline steps have hyperparameter spaces. Enable checkpoints to cut duplicate calculations. Go from research to production environment easily.
Neuraxle Pipelines Code Machine Learning Pipelines - The Right Way. Neuraxle is a Machine Learning (ML) library for building machine learning pipeline
555 Dec 24, 2022