161 Open source projects that are alternatives of or similar to Pbt

MiraiML: asynchronous, autonomous and continuous Machine Learning in Python

Reproducing MuJoCo benchmarks in a modern, commercial game /physics engine (Unity + PhysX).

A curated list of awesome Distributed Deep Learning resources.

Hyperparameter Optimization for TensorFlow, Keras and PyTorch

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

Primitives for machine learning and data science.

These are my notes which I prepared during deep learning specialization taught by AI guru Andrew NG. I have used diagrams and code snippets from the code whenever needed but following The Honor Code.

AutoML frAmework for Neural Networks

An Interactive Approach to Understanding Deep Learning with Keras

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

Efficient Hyperparameter Optimization of Deep Learning Algorithms Using Deterministic RBF Surrogates

Automated modeling and machine learning framework FEDOT

Implementation of ews weight constraint mentioned in recent Deep Mind paper: http://www.pnas.org/content/early/2017/03/13/1611835114.full.pdf

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…

StarCraft II - pysc2 Deep Reinforcement Learning Examples

Easy Hyper Parameter Optimization with mlr and mlrMBO.

StarCraft II Learning Environment

Yes, it's a camel case.

A list of high-quality (newest) AutoML works and lightweight models including 1.) Neural Architecture Search, 2.) Lightweight Structures, 3.) Model Compression, Quantization and Acceleration, 4.) Hyperparameter Optimization, 5.) Automated Feature Engineering.

Bayesian Optimization and Grid Search for xgboost/lightgbm

A toolset for black-box hyperparameter optimisation.

Auto Tune Models - A multi-tenant, multi-data system for automated machine learning (model selection and tuning).

Diviner is a serverless machine learning and hyper parameter tuning platform

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

Implementing reinforcement-learning algorithms for pysc2 -environment

Tensorflow implementation of Gated Conditional Pixel Convolutional Neural Network

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

Python library for CMA Evolution Strategy.

Your local Flux surgeon

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

a distributed Hyperband implementation on Steroids

Iterated Racing for Automatic Algorithm Configuration

🦅Hyperparameter optimization for machine learning pipelines 🦅

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

Autonomous Performance Tuning for Kubernetes !

Reaver: Modular Deep Reinforcement Learning Framework. Focused on StarCraft II. Supports Gym, Atari, and MuJoCo.

A shell-friendly hyperparameter search tool inspired by Optuna

Startcraft II Machine Learning research with DeepMind pysc2 python library .mini-games and agents.

A hyperparameter optimization framework

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

OpenAI Gym wrapper for the DeepMind Control Suite

Experimental Global Optimization Algorithm

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

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

Streamlined machine learning experiment management.

[UNMAINTAINED] Automated machine learning for analytics & production

A fully decentralized hyperparameter optimization framework

Deepmind Recurrent Environment Simulators paper implementation in tensorflow

The open and extensible integrated development environment (IDE) for computer vision with built-in modules for model building, automated labeling, data processing, model training, hyperparameter tuning and workflow orchestration.

Using Kafka-Python to illustrate a ML production pipeline

Keras Implementation of Deepmind's WaveNet for Supervised Learning Tasks

Hyperparameter optimization for PyTorch.

A Repository with C++ implementations of Reinforcement Learning Algorithms (Pytorch)

Spriteworld: a flexible, configurable python-based reinforcement learning environment

This repository focuses on training semantic segmentation models to predict the presence of floodwater for disaster prevention. Models were trained using SageMaker and Colab.

Basic pytorch implementation of NAC/NALU from Neural Arithmetic Logic Units paper by trask et.al

Set model hyperparameters using deterministic, exact algorithms.

A web-based dashboard for Deep Learning

Polyaxon Core Client & CLI to streamline MLOps

Real-time Web Dashboard for Optuna.