112 Open source projects that are alternatives of or similar to optuna-allennlp

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

Set model hyperparameters using deterministic, exact algorithms.

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

A simple, extensible library for developing AutoML systems

Python code for bayesian optimization using Gaussian processes

Distribution transparent Machine Learning experiments on Apache Spark

Toolbox for Bayesian Optimization and Model-Based Optimization in R

BiLSTM-CRF model for NER

Scalable, structured, dynamically-scheduled hyperparameter optimization.

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

[UNMAINTAINED] Automated machine learning for analytics & production

A Clojure machine learning library

AllenNLP Startup Guide

Library for Semi-Automated Data Science

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

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

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

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

Autonomous Performance Tuning for Kubernetes !

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

Real-time Web Dashboard for Optuna.

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

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

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

A toolset for black-box hyperparameter optimisation.

A fully decentralized hyperparameter optimization framework

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

Streamlined machine learning experiment management.

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.

A shell-friendly hyperparameter search tool inspired by Optuna

Bayesian Optimization using GPflow

Using Kafka-Python to illustrate a ML production pipeline

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

🦅Hyperparameter optimization for machine learning pipelines 🦅

Asynchronous Distributed Hyperparameter Optimization.

Utilities and boilerplate code to use wandb with allennlp

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

Machine Learning Tool Box

An automatic ML model optimization tool.

A general-purpose pythonic genetic algorithm.

Gradient based hyperparameter optimization & meta-learning package for TensorFlow

MiraiML: asynchronous, autonomous and continuous Machine Learning in Python

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

Polyaxon Core Client & CLI to streamline MLOps

DeepArchitect: Automatically Designing and Training Deep Architectures

Your local Flux surgeon

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

Parallel Hyperparameter Tuning in Python

Notes for Deep Learning Specialization Courses led by Andrew Ng.

A general, modular, and programmable architecture search framework

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

Hyperparameter optimization package of the mlr3 ecosystem

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

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

OptKeras: wrapper around Keras and Optuna for hyperparameter optimization

Python library for CMA Evolution Strategy.

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

Athens NLP Summer School Labs

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 scikit-learn compatible implementation of hyperband