A fast and simple framework for building and running distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

Automated Machine Learning with scikit-learn

🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.

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

Determined: Deep Learning Training Platform

Sequential Model-based Algorithm Configuration

PaddleSlim is an open-source library for deep model compression and architecture search.

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.

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

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

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.

DeepHyper: Scalable Asynchronous Neural Architecture and Hyperparameter Search for Deep Neural Networks

A collection of pre-trained RL agents using Stable Baselines3, training and hyperparameter optimization included.

Distribution transparent Machine Learning experiments on Apache Spark

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

Hyperparameter search for AllenNLP - powered by Ray TUNE

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

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

An AutoRecSys library for Surprise. Automate algorithm selection and hyperparameter tuning 🚀

Open-Source Recurrent Neural Network Program (RNN). [MATLAB]

hyperparameter search for machine learning

sklearn wrapper for Hyperopt

hyperparameters is a Javascript library for hyperparameter optimization.

Artificial bee colony framework for tuning user-supplied functions

Throw away experiments that don't spark joy

Genetic algorithm framework for tuning arbitrary functions

ray project 中文文档

A wrapper for searching over Neural network architectures, built on top of MXNet framework, in particular gluon.

Sentiment analysis for amazon product reviews using NLTK, Scikit-Learn, and Keras. Using hyperparameter search and LSTM, our best model achieves ~96% accuracy.