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Search results for machine learning hyperparameter tuning
hyperparameter-tuning
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machine-learning
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61 search results found
Nni
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13,725
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
Wandb
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8,204
🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.
Skypilot
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4,975
SkyPilot: Run LLMs, AI, and Batch jobs on any cloud. Get maximum savings, highest GPU availability, and managed execution—all with a simple interface.
Determined
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2,715
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
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2,700
Sequential model-based optimization with a `scipy.optimize` interface
Forecasting
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2,540
Time Series Forecasting Best Practices & Examples
Xcessiv
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1,232
A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python.
Vizier
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1,142
Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
Hyperparameter Optimization Of Machine Learning Algorithms
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1,025
Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)
Onepanel
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704
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.
Evalml
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679
EvalML is an AutoML library written in python.
Hyperparameter_hunter
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635
Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries
Neuraxle
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533
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.
Hyperband
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515
Tuning hyperparams fast with Hyperband
Facet
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483
Human-explainable AI.
Agilerl
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457
Streamlining reinforcement learning with RLOps
Automl Implementation For Static And Dynamic Data Analytics
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443
Implementation/Tutorial of using Automated Machine Learning (AutoML) methods for static/batch and online/continual learning
Syne Tune
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342
Large scale and asynchronous Hyperparameter and Architecture Optimization at your fingertips.
Lale
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321
Library for Semi-Automated Data Science
Sherpa
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294
Hyperparameter optimization that enables researchers to experiment, visualize, and scale quickly.
Mango
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289
Parallel Hyperparameter Tuning in Python
Deeplearning.ai Notes
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271
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.
Renate
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263
Library for automatic retraining and continual learning
Auptimizer
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195
An automatic ML model optimization tool.
Automl_alex
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171
State-of-the art Automated Machine Learning python library for Tabular Data
The Data Science Workshop
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156
A New, Interactive Approach to Learning Data Science
Adatune
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144
Gradient based Hyperparameter Tuning library in PyTorch
Pyxab
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135
PyXAB - A Python Library for X-Armed Bandit and Online Blackbox Optimization Algorithms
Milano
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127
Milano is a tool for automating hyper-parameters search for your models on a backend of your choice.
Sdk
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89
Metadata store for Production ML
Gentun
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80
Hyperparameter tuning for machine learning models using a distributed genetic algorithm
Mlprimitives
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67
Primitives for machine learning and data science.
Hyperbo
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66
Pre-trained Gaussian processes for Bayesian optimization
Hypertune
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60
A library for performing hyperparameter optimization
Mindware
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54
An efficient open-source AutoML system for automating machine learning lifecycle, including feature engineering, neural architecture search, and hyper-parameter tuning.
Ds Ml Public
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49
Python Scripts and Jupyter Notebooks
Scikit Hyperband
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46
A scikit-learn compatible implementation of hyperband
Mlr3tuning
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46
Hyperparameter optimization package of the mlr3 ecosystem
The Deep Learning With Keras Workshop
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40
An Interactive Approach to Understanding Deep Learning with Keras
Edaspy
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30
Estimation of Distribution algorithms Python package
Tune
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30
An abstraction layer for parameter tuning
Spotz
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29
Spark Parameter Optimization and Tuning
Wandb Offline Sync Hook
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26
A convenient way to trigger synchronizations to wandb / Weights & Biases if your compute nodes don't have internet!
Auto Surprise
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25
An AutoRecSys library for Surprise. Automate algorithm selection and hyperparameter tuning 🚀
Mltb
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25
Machine Learning Tool Box
Mlr3mbo
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23
Flexible Bayesian Optimization in R
Skrobot
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19
skrobot is a Python module for designing, running and tracking Machine Learning experiments / tasks. It is built on top of scikit-learn framework.
Bbotk
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18
Black-box optimization framework for R.
Diviner
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17
Diviner is a serverless machine learning and hyper parameter tuning platform
Mlr3hyperband
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17
Successive Halving and Hyperband in the mlr3 ecosystem
Hpbandster Sklearn
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15
A scikit-learn wrapper for HpBandSter hyper parameter search.
Awesome Auto Ml
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13
Awesome list of AutoML frameworks - curated by @oskar-j
Hypertune
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12
Hyperparameter tuning using Particle Swarm Optimization and parallel computation which outperforms current approaches. V0.1 Beta
Dpl
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10
[NeurIPS 2023] Multi-fidelity hyperparameter optimization with deep power laws that achieves state-of-the-art results across diverse benchmarks.
Mlr3tuningspaces
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10
Collection of search spaces for hyperparameter optimization in the mlr3 ecosystem
Easyopt
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9
zero-code hyperparameters optimization framework
Py Hyperpy
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8
HyperaPy: An automatic hyperparameter optimization framework ⚡🚀
Spark Hpopt
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6
Bayesian hyperparamter tuning for Spark MLLib
Diaml
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6
Semi-automated machine learning pipelines
Mlopt
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6
Optimization algorithms for Machine Learning problems like Hyperparameter tuning and Ensembling.
Predicting Indian Stocks Price With Stacked Lstm
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6
Predicting Indian stock prices using Stacked LSTM model. Analysing Reliance, Tata Steel, HDFC Bank, Infosys data. Data prep, EDA, hyperparameter tuning.
Neurosymbolic Tinyml
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5
TinyNS: Platform-Aware Neurosymbolic Auto Tiny Machine Learning
Mltb2
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5
Machine Learning Toolbox 2
Hptuning
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5
Machine Learning Hyper-parameter Tuning processes
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1-61 of 61 search results
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