Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

Automated Machine Learning with scikit-learn

The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.

A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.

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

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

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

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

OCTIS: Comparing Topic Models is Simple! A python package to optimize and evaluate topic models (accepted at EACL2021 demo track)

Library for Semi-Automated Data Science

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

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 enviro…

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

🔬 Some personal research code on analyzing CNNs. Started with a thorough exploration of Stanford's Tiny-Imagenet-200 dataset.

Population Based Training (in PyTorch with sqlite3). Status: Unsupported

syftr is an agent optimizer that helps you find the best agentic workflows for your budget.

Distribution transparent Machine Learning experiments on Apache Spark

Использование MLflow для трекинга экспериментов PyTorch и Sklearn

Structure, sample, and savor hyperparameter searches.

Code examples for https://blog.floydhub.com/guide-to-hyperparameters-search-for-deep-learning-models/