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

Polyaxon Core Client & CLI to streamline MLOps

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

🦅Hyperparameter optimization for machine learning pipelines 🦅

Distribution transparent Machine Learning experiments on Apache Spark

Asynchronous Distributed Hyperparameter Optimization.

🚀 A demonstration of hyperparameter optimization using Optuna for models implemented with AllenNLP.

Hyperparameter optimization package of the mlr3 ecosystem

Robyn is an experimental, automated and open-sourced Marketing Mix Modeling (MMM) package from Facebook Marketing Science. It uses various machine learning techniques (Ridge regression with cross validation, multi-objective evolutionary algorithm for hyperparameter optimisation, gradient-based optimisation for budget allocation etc.) to define m…

Bayesian Optimization using GPflow

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

Streamlined machine learning experiment management.

An automatic ML model optimization tool.

Black box hyperparameter optimization made easy.

A general-purpose pythonic genetic algorithm.

Automated modeling and machine learning framework FEDOT

Parallel Hyperparameter Tuning in Python

MiraiML: asynchronous, autonomous and continuous Machine Learning in Python

OptKeras: wrapper around Keras and Optuna for hyperparameter optimization

本人多次机器学习与大数据竞赛Top5的经验总结，满满的干货，拿好不谢

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.

⚡️ AllenNLP plugin for adding subcommands to use Optuna, making hyperparameter optimization easy

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

Yes, it's a camel case.

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

Your local Flux surgeon

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

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

Simplifying the definition and execution, scaling and deployment of pipelines on the cloud.

Using Kafka-Python to illustrate a ML production pipeline

Intelligently optimizes technical indicators and optionally selects the least intercorrelated for use in machine learning models

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

Large scale and asynchronous Hyperparameter Optimization at your fingertip.

Set model hyperparameters using deterministic, exact algorithms.

A curated list of automated machine learning papers, articles, tutorials, slides and projects

Real-time Web Dashboard for Optuna.

Python library for CMA Evolution Strategy.

Scalable, structured, dynamically-scheduled hyperparameter optimization.

A library for performing hyperparameter optimization

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

Distributed Asynchronous Hyperparameter Optimization better than HyperOpt. 比HyperOpt更强的分布式异步超参优化库。

A scikit-learn compatible implementation of hyperband

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

A Clojure machine learning library

Autonomous Performance Tuning for Kubernetes !

Python code for bayesian optimization using Gaussian processes

Easy Hyper Parameter Optimization with mlr and mlrMBO.

Library for Semi-Automated Data Science

A shell-friendly hyperparameter search tool inspired by Optuna

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

Auto-tune the Entropy Temperature of Soft Actor-Critic via Metagradient - 7th ICML AutoML workshop 2020

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

Machine Learning Tool Box

Toolbox for Bayesian Optimization and Model-Based Optimization in R

Python library for Bayesian hyper-parameters optimization

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

AutoGluon: AutoML for Text, Image, and Tabular Data

A curated list of awesome Distributed Deep Learning resources.

An efficient open-source AutoML system for automating machine learning lifecycle, including feature engineering, neural architecture search, and hyper-parameter tuning.

Hyperparameter optimization in Julia.

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