hyperparameter-tuning
There are 1507 repositories under hyperparameter-tuning topic.
microsoft/nni
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
wandb/wandb
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
skypilot-org/skypilot
Run, manage, and scale AI workloads on any AI infrastructure. Use one system to access & manage all AI compute (Kubernetes, 17+ clouds, or on-prem).
automl/auto-sklearn
Automated Machine Learning with scikit-learn
amanchadha/coursera-deep-learning-specialization
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
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.
scikit-optimize/scikit-optimize
Sequential model-based optimization with a `scipy.optimize` interface
DLR-RM/rl-baselines3-zoo
A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
kubeflow/katib
Automated Machine Learning on Kubernetes
google/vizier
Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
LiYangHart/Hyperparameter-Optimization-of-Machine-Learning-Algorithms
Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)
automl/SMAC3
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization
araffin/rl-baselines-zoo
A collection of 100+ pre-trained RL agents using Stable Baselines, training and hyperparameter optimization included.
alteryx/evalml
EvalML is an AutoML library written in python.
AgileRL/AgileRL
Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools, with 10x faster training through evolutionary hyperparameter optimization.
MIND-Lab/OCTIS
OCTIS: Comparing Topic Models is Simple! A python package to optimize and evaluate topic models (accepted at EACL2021 demo track)
onepanelio/onepanel
The open source, end-to-end computer vision platform. Label, build, train, tune, deploy and automate in a unified platform that runs on any cloud and on-premises.
HunterMcGushion/hyperparameter_hunter
Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries
Western-OC2-Lab/AutoML-Implementation-for-Static-and-Dynamic-Data-Analytics
Implementation/Tutorial of using Automated Machine Learning (AutoML) methods for static/batch and online/continual learning
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.
zygmuntz/hyperband
Tuning hyperparams fast with Hyperband
BCG-X-Official/facet
Human-explainable AI.
ray-project/tune-sklearn
A drop-in replacement for Scikit-Learn’s GridSearchCV / RandomizedSearchCV -- but with cutting edge hyperparameter tuning techniques.
ARM-software/mango
Parallel Hyperparameter Tuning in Python
syne-tune/syne-tune
Large scale and asynchronous Hyperparameter and Architecture Optimization at your fingertips.
IBM/lale
Library for Semi-Automated Data Science
sherpa-ai/sherpa
Hyperparameter optimization that enables researchers to experiment, visualize, and scale quickly.
WarBean/hyperboard
A web-based dashboard for Deep Learning
awslabs/Renate
Library for automatic retraining and continual learning
awslabs/adatune
Gradient based Hyperparameter Tuning library in PyTorch
ppant/deeplearning.ai-notes
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.
DataCanvasIO/Hypernets
A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.
lettergram/sentence-classification
Sentence Classifications with Neural Networks
Alex-Lekov/AutoML_Alex
State-of-the art Automated Machine Learning python library for Tabular Data
jsingh811/pyAudioProcessing
Audio feature extraction and classification
Mattdl/CLsurvey
Continual Hyperparameter Selection Framework. Compares 11 state-of-the-art Lifelong Learning methods and 4 baselines. Official Codebase of "A continual learning survey: Defying forgetting in classification tasks." in IEEE TPAMI.