hyperparameter-search

There are 69 repositories under hyperparameter-search topic.

  • ray-project/ray

    Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

    Language:Python31.7k47217.8k5.4k
  • wandb

    wandb/wandb

    🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.

    Language:Python8.5k543.2k621

  • automl/auto-sklearn

    Automated Machine Learning with scikit-learn

    Language:Python7.5k2151k1.3k
  • determined

    determined-ai/determined

    Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.

    Language:Go2.9k80369348

  • scikit-optimize/scikit-optimize

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

    Language:Python2.7k64647548
  • rl-baselines3-zoo

    DLR-RM/rl-baselines3-zoo

    A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.

    Language:Python1.9k22245486
  • rl-baselines-zoo

    araffin/rl-baselines-zoo

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

    Language:Python1.1k3286206
  • SMAC3

    automl/SMAC3

    SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

    Language:Python1k41516217
  • OCTIS

    MIND-Lab/OCTIS

    OCTIS: Comparing Topic Models is Simple! A python package to optimize and evaluate topic models (accepted at EACL2021 demo track)

    Language:Python6971410297
  • Neuraxle

    Neuraxio/Neuraxle

    The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments.

    Language:Python5991931760
  • sherpa

    sherpa-ai/sherpa

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

    Language:JavaScript328115853

  • IBM/lale

    Library for Semi-Automated Data Science

    Language:Python324236182

  • deephyper/deephyper

    DeepHyper: Scalable Asynchronous Neural Architecture and Hyperparameter Search for Deep Neural Networks

    Language:Python2661814460

  • MattKleinsmith/pbt

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

    Language:Python16512925

  • guillaume-chevalier/Hyperopt-Keras-CNN-CIFAR-100

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

    Language:Python10610276

  • rmccorm4/Tiny-Imagenet-200

    🔬 Some personal research code on analyzing CNNs. Started with a thorough exploration of Stanford's Tiny-Imagenet-200 dataset.

    Language:Python915228

  • logicalclocks/maggy

    Distribution transparent Machine Learning experiments on Apache Spark

    Language:Python89112014

  • vthorey/benderopt

    Black-box optimization library

    Language:Jupyter Notebook86986

  • ChristophAlt/tuna

    Hyperparameter search for AllenNLP - powered by Ray TUNE

    Language:Python28502

  • ISG-Siegen/Auto-Surprise

    An AutoRecSys library for Surprise. Automate algorithm selection and hyperparameter tuning :rocket:

    Language:Python26252

  • ksachdeva/scikit-nni

    AutoML - Hyper parameters search for scikit-learn pipelines using Microsoft NNI

    Language:Python23103

  • ahundt/sharpDARTS

    sharpDARTS: Faster and More Accurate Differentiable Architecture Search

    Language:Python16514

  • edong6768/Malet

    🔨 Malet (Machine Learning Experiment Tool) is a tool for efficient machine learning experiment execution, logging, analysis, and plot making.

    Language:Python16101

  • hyeonsangjeon/Hyperparameters-Optimization

    Hyperparameters-Optimization

    Language:Jupyter Notebook16402

  • floydhub/hyperparameters-search-examples

    Code examples for https://blog.floydhub.com/guide-to-hyperparameters-search-for-deep-learning-models/

    Language:Jupyter Notebook11606

  • jonzia/NeuralNetStudio

    Platform + GUI for hyperparameter optimization of recurrent neural networks (MATLAB).

    Language:MATLAB10203

  • holgern/scikit-optimize

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

    Language:Python8222

  • ihamdi/Covid-xRay-Classification

    Using Pytorch Lightning and Torchxrayvision's Pretrained Densenet121 Models

    Language:Python8200

  • rtflynn/NLP-Sentiment

    Sentiment analysis for amazon product reviews using NLTK, Scikit-Learn, and Keras. Using hyperparameter search and LSTM, our best model achieves ~96% accuracy.

    Language:Python6115

  • Senmumu/ray_project_doc

    ray project 中文文档

    Language:Python5311

  • DrMatters/hyperoptsearchcv

    sklearn wrapper for Hyperopt

    Language:Python4102

  • ealcobaca/mlglass

    We share in this repository some codes and data used during our research about glass property prediction and the design of new glasses.

    Language:Jupyter Notebook4402

  • imoneoi/xrl-script

    Efficient AutoRL script for any framework

    Language:Python4200

  • martin-stoyanov/hyperparameters-site

    hyperparameters is a Javascript library for hyperparameter optimization.

    Language:JavaScript4201

  • ndgigliotti/cluster-optimizer

    A GridSearchCV-like hyperparameter optimizer for clustering (no cross-validation).

    Language:Jupyter Notebook4111

  • tjkessler/pygenetics

    Genetic algorithm framework for tuning arbitrary functions

    Language:Python4301