Comparing Feature Selection Scripts
In this series about feature selection, the first three posts covered three different WhizzML scripts that can help you with this
Category: Product
Powering the Next Wave of Intelligent Devices with Machine Learning – Part 2
In the first part of this series, we introduced the BigML Node-RED bindings and showed how to install and use
Automated Best-First Feature Selection
In this third post about feature selection scripts in WhizzML, we will introduce the third and final algorithm, Best-First Feature Selection
Powering the Next Wave of Intelligent IoT Devices with Machine Learning – Part 1
At BigML, we strive to bring the power of Machine Learning to as many diverse environments as possible. Now you
Simple Boruta Feature Selection Scripting
In the previous post of this series about feature selection WhizzML scripts, we introduced the problem of having too many
Practical Recursive Feature Selection
With the Summer 2018 Release Data Transformations were added to BigML. SQL-style queries, feature engineering with the Flatline editor and options to merge and join datasets
Principal Component Analysis Webinar Video: Dimensionality Reduction Made Easy!
BigML has brought Principal Component Analysis (PCA) to the platform. PCA is a key unsupervised Machine Learning technique used to
Principal Component Analysis: Technical Overview
This past week we’ve been blogging about BigML’s new Principal Component Analysis (PCA) feature. In this post, we will continue
Automating Principal Component Analysis
Today’s post is the fifth one of our series of blog posts about BigML Principal Component Analysis (PCA) unique implementation, the latest
A REST API for Principal Component Analysis
As part of our PCA release, we have released a series of blog posts, including a use case and a
