auto-sklearn - Automated Machine Learning with scikit-learn

•    Python

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auto-sklearn is an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator.

automl scikit-learn automated-machine-learning hyperparameter-optimization hyperparameter-tuning hyperparameter-search bayesian-optimization metalearning meta-learning smac

determined - Determined: Deep Learning Training Platform

•    Python

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Determined integrates these features into an easy-to-use, high-performance deep learning environment — which means you can spend your time building models instead of managing infrastructure. To use Determined, you can continue using popular DL frameworks such as TensorFlow and PyTorch; you just need to update your model code to integrate with the Determined API.

kubernetes machine-learning deep-learning tensorflow pytorch hyperparameter-optimization hyperparameter-tuning hyperparameter-search distributed-training ml-infrastructure ml-platform

client - 🔥 A tool for visualizing and tracking your machine learning experiments

•    Python

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Use W&B to build better models faster. Track and visualize all the pieces of your machine learning pipeline, from datasets to production models. If you have any questions, please don't hesitate to ask in our Slack community.

machine-learning reinforcement-learning deep-learning tensorflow keras pytorch hyperparameter-search experiment-track

PaddleSlim - PaddleSlim is an open-source library for deep model compression and architecture search

•    Python

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PaddleSlim is an open-source library for deep model compression and architecture search.

pruning quantization nas knowledge-distillation model-compression neural-architecture-search hyperparameter-search autodl

Ray - A unified framework for scaling AI and Python applications

•    Python

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Ray is an open-source unified compute framework that makes it easy to scale AI and Python workloads — from reinforcement learning to deep learning to tuning, and model serving. Ray is a unified way to scale Python and AI applications from a single node to a cluster.

data-science machine-learning reinforcement-learning deep-learning deployment tensorflow optimization parallel pytorch distributed model-selection automl hyperparameter-search rllib

SMAC3 - Sequential Model-based Algorithm Configuration

•    Python

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Attention: This package is under heavy development and subject to change. A stable release of SMAC (v2) in Java can be found here. The documentation can be found here.

bayesian-optimization bayesian-optimisation hyperparameter-optimization hyperparameter-tuning hyperparameter-search configuration algorithm-configuration automl automated-machine-learning

rl-baselines3-zoo - A collection of pre-trained RL agents using Stable Baselines3, training and hyperparameter optimization included

•    Python

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RL Baselines3 Zoo is a training framework for Reinforcement Learning (RL), using Stable Baselines3. It provides scripts for training, evaluating agents, tuning hyperparameters, plotting results and recording videos.

reinforcement-learning robotics optimization lab openai gym hyperparameter-optimization rl sde hyperparameter-tuning hyperparameter-search pybullet stable-baselines pybullet-environments tuning-hyperparameters

Hyperopt-Keras-CNN-CIFAR-100 - Auto-optimizing a neural net (and its architecture) on the CIFAR-100 dataset

•    Python

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This project acts as both a tutorial and a demo to using Hyperopt with Keras, TensorFlow and TensorBoard. Not only we try to find the best hyperparameters for the given hyperspace, but also we represent the neural network architecture as hyperparameters that can be tuned. This automates the process of searching for the best neural architecture configuration and hyperparameters. Here, we are meta-optimizing a neural net and its architecture on the CIFAR-100 dataset (100 fine labels), a computer vision task. This code could be easily transferred to another vision dataset or even to another machine learning task.

hyperopt hyperparameter-optimization hyperparameter-tuning hyperparameters-optimization hyperparameter-search keras cnn cnn-keras tensorflow