Other packages > Find by keyword >

kerastuneR  

Interface to 'Keras Tuner'
View on CRAN: Click here


Download and install kerastuneR package within the R console
Install from CRAN:
install.packages("kerastuneR")

Install from Github:
library("remotes")
install_github("cran/kerastuneR")

Install by package version:
library("remotes")
install_version("kerastuneR", "0.1.0.7")



Attach the package and use:
library("kerastuneR")
Maintained by
Turgut Abdullayev
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-03-20
Latest Update: 2023-09-03
Description:
'Keras Tuner' is a hypertuning framework made for humans. It aims at making the life of AI practitioners, hypertuner algorithm creators and model designers as simple as possible by providing them with a clean and easy to use API for hypertuning. 'Keras Tuner' makes moving from a base model to a hypertuned one quick and easy by only requiring you to change a few lines of code.
How to cite:
Turgut Abdullayev (2020). kerastuneR: Interface to 'Keras Tuner'. R package version 0.1.0.7, https://cran.r-project.org/web/packages/kerastuneR. Accessed 22 Dec. 2024.
Previous versions and publish date:
0.1.0.1 (2020-03-20 09:30), 0.1.0.2 (2020-05-14 10:10), 0.1.0.3 (2020-10-04 15:30), 0.1.0.4 (2022-01-10 17:02), 0.1.0.5 (2022-03-25 09:50), 0.1.0.6 (2023-09-03 20:40)
Other packages that cited kerastuneR R package
View kerastuneR citation profile
Other R packages that kerastuneR depends, imports, suggests or enhances
Complete documentation for kerastuneR
Downloads during the last 30 days
Get rewarded with contribution points by helping add
Reviews / comments / questions /suggestions ↴↴↴

Today's Hot Picks in Authors and Packages

wordspace  
Distributional Semantic Models in R
An interactive laboratory for research on distributional semantic models ('DSM', see < ...
Download / Learn more Package Citations See dependency  
quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  
dmlalg  
Double Machine Learning Algorithms
Implementation of double machine learning (DML) algorithms in R, based on Emmenegger and Buehlmann ...
Download / Learn more Package Citations See dependency  
composits  
Compositional, Multivariate and Univariate Time Series Outlier Ensemble
A compositional multivariate and univariate time series outlier ensemble.It uses the four R packages ...
Download / Learn more Package Citations See dependency  
elect  
Estimation of Life Expectancies Using Multi-State Models
Functions to compute state-specific and marginal life expectancies. The computation is based on a fi ...
Download / Learn more Package Citations See dependency  
LOGANTree  
Tree-Based Models for the Analysis of Log Files from Computer-Based Assessments
Enables researchers to model log-file data from computer-based assessments using machine-learning te ...
Download / Learn more Package Citations See dependency  
Maintainer: Qi Qin (view profile)

23,394

R Packages

201,798

Dependencies

63,416

Author Associations

23,395

Publication Badges

© Copyright 2022 - present. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA