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Search results for tuning parameters
tuning-parameters
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19 search results found
Mlj.jl
⭐
1,690
A Julia machine learning framework
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)
Awesome Mysql Performance
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444
🔥 A curated list of awesome links related to MySQL / MariaDB / Percona performance tuning
Hypersearch
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352
Hyperparameter optimization for PyTorch.
Mango
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289
Parallel Hyperparameter Tuning in Python
Tscv
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226
Time Series Cross-Validation -- an extension for scikit-learn
Accera
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59
Open source cross-platform compiler for compute-intensive loops used in AI algorithms, from Microsoft Research
Hifi Maximizer Mod
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50
A Magisk module for maximizing the digital audio fidelity by reducing jitters on audio outputs (USB DACs, Bluetooth a2dp, DLNA, etc.)
Mlbayesopt
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39
R package to tune parameters for machine learning(Support Vector Machine, Random Forest, and Xgboost), using bayesian optimization with gaussian process
Keras Hypetune
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33
A friendly python package for Keras Hyperparameters Tuning based only on NumPy and hyperopt.
Stremr
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31
Streamlined Estimation for Static, Dynamic and Stochastic Treatment Regimes in Longitudinal Data
Mlrhyperopt
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31
Easy Hyper Parameter Optimization with mlr and mlrMBO.
Distributed Translation Infrastructure
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11
The distributed statistical machine translation infrastructure consisting of load balancing, text pre/post-processing and translation services. Written in C++ 11 and utilises multicore CPUs by employing multi-threading, allows for secure SSL/TLS communications.
Lightcurvesclassifier
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8
Package for machine learning of astronomical objects such as light curves
A Sparse Coding Based Approach For Class Specific Feature Selection
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8
A novel Sparse-Coding Based Approach Feature Selection with emphasizing joint l_1,2-norm minimization and the Class-Specific Feature Selection.
Pid Pida Gatuning
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7
Implementation of a genetic algorithm to determine the parameters of the PID, PI-D, I-PD and PIDA controllers in order to compensate various benchmark processes, which are representative of many industrial applications. In particular, by considering separately a set-point and a load disturbance rejection unit step response the IAE is minimized by constraining the maximum sensitivity.
Hptuning
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5
Machine Learning Hyper-parameter Tuning processes
Mcnntunes
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5
Tuning Monte Carlo generators with machine learning.
1-19 of 19 search results
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