102 Open source projects that are alternatives of or similar to hone

DeepArchitect: Automatically Designing and Training Deep Architectures

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

An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

Gradient based hyperparameter optimization & meta-learning package for TensorFlow

A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python.

OptKeras: wrapper around Keras and Optuna for hyperparameter optimization

Notes for Deep Learning Specialization Courses led by Andrew Ng.

A general-purpose pythonic genetic algorithm.

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

A Python library for the state-of-the-art Bayesian optimization algorithms, with the core implemented in C++.

An automatic ML model optimization tool.

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

Hyperparameter optimization package of the mlr3 ecosystem

Time Series Cross-Validation -- an extension for scikit-learn

Distribution transparent Machine Learning experiments on Apache Spark

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

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

Bilevel Optimization Library in Python for Multi-Task and Meta Learning

A simple collection of well working NLP models (Keras, H2O, StarSpace) tuned and benchmarked on a variety of datasets.

A general, modular, and programmable architecture search framework

Bayesian Optimization using GPflow

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

Polyaxon Core Client & CLI to streamline MLOps

Purely functional genetic algorithms for multi-objective optimisation

Asynchronous Distributed Hyperparameter Optimization.

Toolbox for Bayesian Optimization and Model-Based Optimization in R

MIT DeepTraffic top 2% solution (75.01 mph) 🚗.

Scalable, structured, dynamically-scheduled hyperparameter optimization.

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

Using Kafka-Python to illustrate a ML production pipeline

A simple, extensible library for developing AutoML systems

A library for doing Bayesian Optimization using Gaussian Processes (blackbox optimizer) in Go/Golang.

mlmodels : Machine Learning and Deep Learning Model ZOO for Pytorch, Tensorflow, Keras, Gluon models...

A friendly python package for Keras Hyperparameters Tuning based only on NumPy and hyperopt.

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

A scikit-learn compatible implementation of hyperband

State-of-the art Automated Machine Learning python library for Tabular Data

This repo contains the underlying code for all the experiments from the paper: "Automatic Discovery of Privacy-Utility Pareto Fronts"

[UNMAINTAINED] Automated machine learning for analytics & production

A Clojure machine learning library

A toolset for black-box hyperparameter optimisation.

Machine Learning Tool Box

A fully decentralized hyperparameter optimization framework

Python code for bayesian optimization using Gaussian processes

Hyperparameter Optimization for TensorFlow, Keras and PyTorch

Set model hyperparameters using deterministic, exact algorithms.

Efficient Hyperparameter Optimization of Deep Learning Algorithms Using Deterministic RBF Surrogates

Library for Semi-Automated Data Science

Python library for CMA Evolution Strategy.

PyTorch implementation of Proximal Gradient Algorithms a la Parikh and Boyd (2014). Useful for Auto-Sizing (Murray and Chiang 2015, Murray et al. 2019).

Determined: Deep Learning Training Platform

Notes, 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

Simple, but essential Bayesian optimization package

Real-time Web Dashboard for Optuna.

A hyperparameter optimization and data collection toolbox for convenient and fast prototyping of machine-learning models.

Examples for https://github.com/optuna/optuna

Your local Flux surgeon

Streamlined machine learning experiment management.

Parallel Hyperparameter Tuning in Python

Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization