Popular GitHub Repositories for Hyperparameter Tuning

Automated Machine Learning with scikit-learn

A comprehensive collection of data analysis and machine learning projects, showcasing techniques and models for various data challenges. Dive in to explore code examples, analyses, and machine learning workflows.

Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.

Automated Machine Learning on Kubernetes

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

EvalML is an AutoML library written in python.

The open source, end-to-end computer vision platform. Label, build, train, tune, deploy and automate in a unified platform that runs on any cloud and on-premises.

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.

Tuning hyperparams fast with Hyperband

Large scale and asynchronous Hyperparameter and Architecture Optimization at your fingertips.

Hyperparameter optimization that enables researchers to experiment, visualize, and scale quickly.

Library for automatic retraining and continual learning

Gradient based Hyperparameter Tuning library in PyTorch

These 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.

A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.

An automatic ML model optimization tool.

Milano is a tool for automating hyper-parameters search for your models on a backend of your choice.

Auto-optimizing a neural net (and its architecture) on the CIFAR-100 dataset. Could be easily transferred to another dataset or another classification task.

Distribution transparent Machine Learning experiments on Apache Spark

Nomadic is an enterprise-grade framework for teams to continuously optimize compound AI systems