196 Open source projects that are alternatives of or similar to ml-pipeline

Machine Learning Tool Box

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

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

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

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

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

[UNMAINTAINED] Automated machine learning for analytics & production

A 100%-Julia implementation of Gradient-Boosting Regression Tree algorithms

🌳 Stacked Gradient Boosting Machines

Building Decision Trees From Scratch In Python

Bayesian Optimization using GPflow

Projects developed by Domino's R&D team

A lightweight tool to get an AI Infrastructure Stack up in minutes not days. K3ai will take care of setup K8s for You, deploy the AI tool of your choice and even run your code on it.

支持百度竞赛数据的中文事件抽取，支持ace2005数据的英文事件抽取，本人将苏神的三元组抽取算法中的DGCNN改成了事件抽取任务，并将karas改成了本人习惯使用的pytorch，在数据加载处考虑了各种语言的扩展

Earthquake Prediction Challenge with LightGBM and XGBoost

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.

Scalable, structured, dynamically-scheduled hyperparameter optimization.

Automatic machine learning for tabular data. ⚡🔥⚡

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

MLFLow Tracking Server based on Docker and AWS S3

Hyperparameter optimization package of the mlr3 ecosystem

Asynchronous Distributed Hyperparameter Optimization.

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

GoCD plugins to work with MLFlow as model repository in a CD flow

An automatic ML model optimization tool.

Gradient based hyperparameter optimization & meta-learning package for TensorFlow

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

Real-time Web Dashboard for Optuna.

Keras implementation of CNN, DeepConvLSTM, and SDAE and LightGBM for sensor-based Human Activity Recognition (HAR).

Ready to run docker-compose configuration for ML Flow with Mysql and Minio S3

Show how to perform fast retraining with LightGBM in different business cases

Managing machine learning life-cycle with MLflow tutorial

A Clojure machine learning library

Scalable machine 🤖 learning for time series forecasting.

머신러닝/딥러닝(PyTorch, TensorFlow) 전용 도커입니다. 한글 폰트, 한글 자연어처리 패키지(konlpy), 형태소 분석기, Timezone 등의 설정 등을 추가 하였습니다.

Parallel Hyperparameter Tuning in Python

Python code for bayesian optimization using Gaussian processes

PyTorch Lightning + Hydra. A very user-friendly template for rapid and reproducible ML experimentation with best practices. ⚡🔥⚡

Library for Semi-Automated Data Science

Repo that relates to the Medium blog 'Keeping your ML model in shape with Kafka, Airflow' and MLFlow'

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

Distribution transparent Machine Learning experiments on Apache Spark

Comet-For-MLFlow Extension

Set model hyperparameters using deterministic, exact algorithms.

🏆 Kaggle 8th place solution

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

Toolbox for Bayesian Optimization and Model-Based Optimization in R

CartPole game by Reinforcement Learning, a journey from training to inference

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

FuseML aims to provide an MLOps framework as the medium dynamically integrating together the AI/ML tools of your choice. It's an extensible tool built through collaboration, where Data Engineers and DevOps Engineers can come together and contribute with reusable integration code.

A simple, extensible library for developing AutoML systems

A general-purpose pythonic genetic algorithm.

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

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

DeepArchitect: Automatically Designing and Training Deep Architectures

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

📒 Experiment tracking tool and model registry

Evaluate wandb, tensorboard, neptune, mlflow, etc

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

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