Projects in Awesome Lists tagged with hyperparameters

https://github.com/tobegit3hub/advisor

Open-source implementation of Google Vizier for hyper parameters tuning

algorithm automl blackbox dl hyperparameters ml optimization tunning

Last synced: 15 May 2025

https://github.com/araffin/rl-baselines-zoo

A collection of 100+ pre-trained RL agents using Stable Baselines, training and hyperparameter optimization included.

gym hyperparameter-optimization hyperparameter-search hyperparameter-tuning hyperparameters openai openai-gym optimization pybullet reinforcement-learning rl stable-baselines zoo

Last synced: 08 Apr 2025

https://github.com/MaurizioFD/RecSys2019_DeepLearning_Evaluation

This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.

bpr bprmf bprslim collaborative-filtering content-based-recommendation deep-learning evaluation-framework funksvd hybrid-recommender-system hyperparameters knn matrix-completion matrix-factorization neural-network recommendation-algorithms recommendation-system recommender-system reproducibility reproducible-research slimelasticnet

Last synced: 11 May 2025

https://github.com/neuraxio/neuraxle

The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments.

deep-learning framework hyperparameter-optimization hyperparameter-search hyperparameter-tuning hyperparameters machine-learning neuraxle parallel pipeline pipeline-framework python-library scikit-learn

Last synced: 07 Oct 2025

https://github.com/Neuraxio/Neuraxle

The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments.

deep-learning framework hyperparameter-optimization hyperparameter-search hyperparameter-tuning hyperparameters machine-learning neuraxle parallel pipeline pipeline-framework python-library scikit-learn

Last synced: 05 Apr 2025

https://github.com/zygmuntz/hyperband

Tuning hyperparams fast with Hyperband

gradient-boosting gradient-boosting-classifier hyperparameter-optimization hyperparameter-tuning hyperparameters machine-learning

Last synced: 28 Jan 2026

https://github.com/rodrigo-arenas/sklearn-genetic-opt

ML hyperparameters tuning and features selection, using evolutionary algorithms.

artificial-intelligence automl begginer-friendly contributions-welcome deap evolutionary-algorithms feature-selection featureselection good-first-issue goodfirstissue help-wanted hyperparameter-optimization hyperparameters looking-for-contributors machine-learning model-selection python scikit-learn sklearn up-for-grabs

Last synced: 15 May 2025

https://github.com/gyrdym/ml_algo

Machine learning algorithms in Dart programming language

algorithm batch-gradient-descent classifier dart dartlang data-science hyperparameters lasso-regression linear-regression logistic-regression machine-learning machine-learning-algorithms mini-batch-gradient-descent regression sgd softmax softmax-algorithm softmax-classifier softmax-regression stochastic-gradient-descent

Last synced: 06 Apr 2025

https://github.com/openmole/openmole

Workflow engine for exploration of simulation models using high throughput computing

dirac distributed-computing egi grid hyperparameters modeling-tool parameter-estimation parameter-search parameter-tuning scala scientific-computing workflow workflow-engine

Last synced: 11 Oct 2025

https://github.com/PetrochukM/HParams

Configure Python functions explicitly and safely

configuration deep-learning hyperparameters machine-learning python python3

Last synced: 05 Apr 2025

https://github.com/seba-1511/randopt

Streamlined machine learning experiment management.

experiments hyperparameter-optimization hyperparameters visualization

Last synced: 23 Apr 2025

https://github.com/joydeepmedhi/anchor-boxes-with-kmeans

How to initialize Anchors in Faster RCNN for custom dataset?

anchor anchor-box aspect-ratio bounding-boxes clusters computer-vision custom-dataset detection distance-metric faster-rcnn hyperparameters iou kmeans object-detection python tensorflow-models

Last synced: 02 May 2025

https://github.com/automl/DeepCAVE

An interactive framework to visualize and analyze your AutoML process in real-time.

analysis automl hyperparameter-importance hyperparameters iml interactive real-time sampling-bias visualization

Last synced: 26 Mar 2025

https://github.com/openmole/mgo

Purely functional genetic algorithms for multi-objective optimisation

functional-programming genetic-algorithm hyperparameter-optimization hyperparameter-tuning hyperparameters optimisation parameter-tuning scala

Last synced: 07 Apr 2025

https://github.com/atanasster/hyperparameters

ES6 hyperparameters search for tfjs

es6 hyperopt hyperparameters javascript tensorflow tensorflowjs tfjs

Last synced: 14 Jun 2025

https://github.com/guybedo/minos

Deep learning, architecture and hyper parameters search with genetic algorithms

deep-learning genetic-algorithm hyperparameters keras-models python tensorflow

Last synced: 12 Apr 2025

https://github.com/eBay/AutoOpt

Automatic and Simultaneous Adjustment of Learning Rate and Momentum for Stochastic Gradient Descent

hyperparameters learning-rate machine-learning momentum optimization pytorch sgd

Last synced: 08 May 2025

https://github.com/himkt/allennlp-optuna

⚡️ AllenNLP plugin for adding subcommands to use Optuna, making hyperparameter optimization easy

allennlp allennlp-subcommand hyperparameter-optimization hyperparameters jsonnet optuna

Last synced: 03 Aug 2025

https://github.com/fluxml/parameterschedulers.jl

Common hyperparameter scheduling for ML

flux hyperparameters machine-learning optimization

Last synced: 27 Feb 2025

https://github.com/minyus/optkeras

OptKeras: wrapper around Keras and Optuna for hyperparameter optimization

deep deep-learning hyperparameter-optimization hyperparameters keras neural-network optuna

Last synced: 01 Oct 2025

https://github.com/mlr-org/paradox

ParamHelpers Next Generation

experimental-design hyperparameters mlr3 r r-package transformations

Last synced: 05 Apr 2025

https://github.com/ksachdeva/scikit-nni

AutoML - Hyper parameters search for scikit-learn pipelines using Microsoft NNI

automl hyperparameter-search hyperparameters neural-network-intelligence nni scikit-learn scikit-learn-api sklearn sklearn-library tool

Last synced: 23 Oct 2025

https://github.com/rohan-varma/neuralnets

🤖 bare-bones implementation of a neural network with numpy

hyperparameters momentum neural-network

Last synced: 06 May 2025

https://github.com/neptune-ai/neptune-optuna

🚀 Optuna visualization dashboard that lets you log and monitor hyperparameter sweep live.

compare experiment hyperparameters management mlops optimization parameters plot plots tracker tracking tuning visualize viz

Last synced: 13 Apr 2025

https://github.com/bhattbhavesh91/svm-c-gamma-hyperparameters-tutorial

In this video, I'll try to explain the hyperparameters C & Gamma in Support Vector Machine (SVM) in the simplest possible way.

hyperparameter-optimization hyperparameters svm svm-classifier svm-hyperparameters svm-kernel svm-model video

Last synced: 03 Aug 2025

https://github.com/michalwols/hp

A python library for managing Hyperparameters

argparse argument-parser hyperparameters machine-learning python

Last synced: 20 Mar 2025

https://github.com/andreacasalino/gaussianprocesses

Modern C++ library handling gaussian processes

cpp cpp17 eigen gaussian gaussian-distribution gaussian-process-regression gaussian-processes hyperparameter-optimization hyperparameters training

Last synced: 24 Oct 2025

https://github.com/juselara1/yacmmal

Yet Another Config Manager for MAchine Learning (yacmmal) is a package to automatically load config files for machine learning projects.

conf config data-class hyperparameters json loader machine-learning toml yaml

Last synced: 04 Sep 2025

https://github.com/anishlearnstocode/improving-deep-neural-networks

Coursera Course: Improving Deep Neural Networks, part of the Deep Learning Specialization ~deeplearning.ai

coursera deep-learning hyperparameters neural-networks optimization regularization solutions

Last synced: 10 Apr 2025

https://github.com/fitushar/cyclical-learning-rates-for-training-neural-networks-with-unbalanced-data-sets

As the learning rate is one of the most important hyper-parameters to tune for training convolutional neural networks. In this paper, a powerful technique to select a range of learning rates for a neural network that named cyclical learning rate was implemented with two different skewness degrees. It is an approach to adjust where the value is cycled between a lower bound and upper bound. CLR policies are computationally simpler and can avoid the computational expense of fine tuning with fixed learning rate. It is clearly shown that changing the learning rate during the training phase provides by far better results than fixed values with similar or even smaller number of epochs.

clr clr-policies cnn cyclical-learning-rates epochs expense hyperparameters learning-rate learning-rates neural-network range skewness-degrees