460 Open source projects that are alternatives of or similar to scikit-hyperband

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.

Library for Semi-Automated Data Science

A library for performing hyperparameter optimization

Automated Machine Learning with scikit-learn

Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries

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

An automatic ML model optimization tool.

An Interactive Approach to Understanding Deep Learning with Keras

AutoGluon: AutoML for Text, Image, and Tabular Data

Large scale and asynchronous Hyperparameter Optimization at your fingertip.

Black box hyperparameter optimization made easy.

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

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

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

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

Sequential Model-based Algorithm Configuration

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

Distribution transparent Machine Learning experiments on Apache Spark

A drop-in replacement for Scikit-Learn’s GridSearchCV / RandomizedSearchCV -- but with cutting edge hyperparameter tuning techniques.

Hyperparameter optimization in Julia.

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

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

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

skrobot is a Python module for designing, running and tracking Machine Learning experiments / tasks. It is built on top of scikit-learn framework.

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

Polyaxon Core Client & CLI to streamline MLOps

🦅Hyperparameter optimization for machine learning pipelines 🦅

Purely functional genetic algorithms for multi-objective optimisation

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

Iterated Racing for Automatic Algorithm Configuration

Automated Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning 🚀

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

Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)

A general-purpose pythonic genetic algorithm.

Parallel Hyperparameter Tuning in Python

Machine Learning Tool Box

Hyperparameter optimization package of the mlr3 ecosystem

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

Tuning hyperparams fast with Hyperband

[UNMAINTAINED] Automated machine learning for analytics & production

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

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

Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.

A Clojure machine learning library

基于情感字典和机器学习的股市舆情情感分类可视化Web

MLOps Platform

I am taking up the #100DaysOfMLCode Challenge 😎

A scikit-learn compatible library for anomaly detection

Hummingbird compiles trained ML models into tensor computation for faster inference.

Convert scikit-learn models and pipelines to ONNX

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.

A library for debugging/inspecting machine learning classifiers and explaining their predictions

Formed trajectories of sets of points.Experimented on finding similarities between trajectories based on DTW (Dynamic Time Warping) and LCSS (Longest Common SubSequence) algorithms.Modeled trajectories as strings based on a Grid representation.Benchmarked KNN, Random Forest, Logistic Regression classification algorithms to classify efficiently t…

Class-imbalanced / Long-tailed ensemble learning in Python. Modular, flexible, and extensible. | 模块化、灵活、易扩展的类别不平衡/长尾机器学习库

All the slides, accompanying code and exercises all stored in this repo. 🎈

A Case Study Approach to Successful Data Science Projects Using Python, Pandas, and Scikit-Learn

Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code.

🍊 📊 💡 Orange: Interactive data analysis

An experiment about re-implementing supervised learning models based on shallow neural network approaches (e.g. fastText) with some additional exclusive features and nice API. Written in Python and fully compatible with Scikit-learn.