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

A scikit-learn compatible implementation of hyperband

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

Polyaxon Core Client & CLI to streamline MLOps

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.

Automated Machine Learning with scikit-learn

Library for Semi-Automated Data Science

Parallel Hyperparameter Tuning in Python

Helm charts for creating reproducible and maintainable deployments of Polyaxon with Kubernetes.

A general-purpose pythonic genetic algorithm.

datascienv is package that helps you to setup your environment in single line of code with all dependency and it is also include pyforest that provide single line of import all required ml libraries

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

Hyperparameter optimization package of the mlr3 ecosystem

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

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

도서 "[개정판] 파이썬 라이브러리를 활용한 머신 러닝"의 주피터 노트북과 코드입니다.

Distribution transparent Machine Learning experiments on Apache Spark

Python Machine Learning (ML) project that demonstrates the archetypal ML workflow within a Jupyter notebook, with automated model deployment as a RESTful service on Kubernetes.

Machine Learning Tool Box

🦅Hyperparameter optimization for machine learning pipelines 🦅