Linear Regression Joins the Suite of Supervised Methods on BigML
The latest BigML release brings a tried and true Machine Learning algorithm to the platform: Linear Regression. We intend to
Tag: Release
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
Principal Component Analysis with the BigML Dashboard: Easy as 1-2-3!
The BigML Team is bringing Principal Component Analysis (PCA) to the BigML platform on December 20, 2018. As explained in our introductory
Applying Dimensionality Reduction with PCA to Cancer Data
Principal Component Analysis (PCA) is a powerful and well-established data transformation method that can be used for data visualization, dimensionality
Principal Component Analysis (PCA): Dimensionality Reduction!
The new BigML release is here! Join us on Thursday, December 20, 2018, at 10:00 AM PST (Portland, Oregon. GMT
The Data Transformations Webinar Video is Here: Machine Learning-Ready Data!
The latest BigML release brings new Data Transformation capabilities to our Machine Learning platform, crucially alleviating the data engineering bottleneck.
Automating Data Transformations with WhizzML and the BigML Python Bindings
This is the fifth post of our series of six about BigML’s new release: Data Transformations. This time we are
Efficient Data Transformations Using the BigML API
As part of our release for Data Transformations, we have outlined both a use case and how to execute the
