Powerful Package for Machine Learning, Hyperparameter Tuning (Grid & Random Search), Shiny App | R-bloggers

Powerful Package for Machine Learning, Hyperparameter Tuning (Grid & Random Search), Shiny App | R-bloggers

Are you interested in guest posting? Publish at DataScience+ via your RStudio editor. Category Advanced Modeling Tags Predictive Modeling R Programming Random Search Shiny I have discovered a new package (at least to me) named Machine Learning Models and Tools for R. The author of this package Brian J Smith describes it as “MachineShop is a meta-package for statistical and machine learning with a unified interface for model fitting, prediction, performance assessment, and presentation of results. Support is provided […]Related Post Parsing HTML and Applying Unsupervised Machine Learning. Part 3: Principal Component Analysis (PCA) using Python Parsing HTML and Applying Unsupervised Machine Learning. Part 2: Applied Clustering Using Python Parsing HTML and Applying Unsupervised Machine Learning. Part 1: HTML Processing using Python Using R to Analyze & Evaluate Survey Data – Part 1 With great powers come great responsibilities: model checks in Bayesian data analysis

8 mentions: @Rbloggers@DerFredo@whoyos21@langstat@LaForge_AI@ds_vault@data_geek_
Date: 2020/05/21 11:13

Referring Tweets

@Rbloggers Powerful Package for Machine Learning, Hyperparameter Tuning (Grid & Random Search), Shiny {t.co/txCtcXEjOP} #rstats #DataScience

Related Entries

Read more Resources for Women in AI, Data Science, and Machine Learning
0 users, 43 mentions 2020/03/08 14:21
Read more Exploring TensorFlow Quantum, Google’s New Framework for Creating Quantum Machine Learning Models
0 users, 12 mentions 2020/03/23 15:51
Read more Understanding Word Embedding Arithmetic: Why there's no single answer to "King - Man + Woman = ?" | ...
1 users, 11 mentions 2020/05/08 16:51
Read more 13 must-read papers from AI experts
0 users, 38 mentions 2020/05/20 17:21
Read more The Best NLP with Deep Learning Course is Free
0 users, 72 mentions 2020/05/22 17:20