Tune SklearnA drop-in replacement for Scikit-Learn’s GridSearchCV / RandomizedSearchCV -- but with cutting edge hyperparameter tuning techniques.
AdatuneGradient based Hyperparameter Tuning library in PyTorch
LaleLibrary for Semi-Automated Data Science
Coursera Deep Learning SpecializationNotes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models
AuptimizerAn automatic ML model optimization tool.
Rl Baselines3 ZooA collection of pre-trained RL agents using Stable Baselines3, training and hyperparameter optimization included.
ForecastingTime Series Forecasting Best Practices & Examples
EvalmlEvalML is an AutoML library written in python.
MilanoMilano is a tool for automating hyper-parameters search for your models on a backend of your choice.
PbtPopulation Based Training (in PyTorch with sqlite3). Status: Unsupported
Automl alexState-of-the art Automated Machine Learning python library for Tabular Data
AmlaAutoML frAmework for Neural Networks
Hyperopt Keras Cnn Cifar 100Auto-optimizing a neural net (and its architecture) on the CIFAR-100 dataset. Could be easily transferred to another dataset or another classification task.
DeterminedDetermined: Deep Learning Training Platform
MgoPurely functional genetic algorithms for multi-objective optimisation
MlprimitivesPrimitives for machine learning and data science.
Rl Baselines ZooA collection of 100+ pre-trained RL agents using Stable Baselines, training and hyperparameter optimization included.
Hyperparameter hunterEasy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries
Smac3Sequential Model-based Algorithm Configuration
HyperbandTuning hyperparams fast with Hyperband
OnepanelThe open and extensible integrated development environment (IDE) for computer vision with built-in modules for model building, automated labeling, data processing, model training, hyperparameter tuning and workflow orchestration.
NeuraxleA 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.
SherpaHyperparameter optimization that enables researchers to experiment, visualize, and scale quickly.
FacetHuman-explainable AI.
Deeplearning.ai NotesThese are my notes which I prepared during deep learning specialization taught by AI guru Andrew NG. I have used diagrams and code snippets from the code whenever needed but following The Honor Code.
Scikit OptimizeSequential model-based optimization with a `scipy.optimize` interface
mindwareAn efficient open-source AutoML system for automating machine learning lifecycle, including feature engineering, neural architecture search, and hyper-parameter tuning.
polystoresA library for performing hyperparameter optimization
Auto-SurpriseAn AutoRecSys library for Surprise. Automate algorithm selection and hyperparameter tuning 🚀
bboptBlack box hyperparameter optimization made easy.
syne-tuneLarge scale and asynchronous Hyperparameter Optimization at your fingertip.
divinerDiviner is a serverless machine learning and hyper parameter tuning platform
mltbMachine Learning Tool Box
iraceIterated Racing for Automatic Algorithm Configuration
maggyDistribution transparent Machine Learning experiments on Apache Spark
map-floodwater-satellite-imageryThis repository focuses on training semantic segmentation models to predict the presence of floodwater for disaster prevention. Models were trained using SageMaker and Colab.
mangoParallel Hyperparameter Tuning in Python
skrobotskrobot is a Python module for designing, running and tracking Machine Learning experiments / tasks. It is built on top of scikit-learn framework.
mlr3tuningHyperparameter optimization package of the mlr3 ecosystem
open-boxGeneralized and Efficient Blackbox Optimization System.
HypernetsA General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.