Preparing Data for Machine Learning with BigML
At BigML we’re well aware that data preparation and feature engineering are key steps for the success of any Machine
Category: Flatline
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
Using a Customized Cost Function to deal with Unbalanced Data
As pointed in this Kdnuggets article, it’s often the case that we only have a few examples of the thing
Feature Selection not only for Programmers
Nowadays, many knowledge workers have access to lots of data that can be analyzed to extract interesting insights. This has brought people
Programmatically Fill in Missing Values in Your Dataset with WhizzML
For new WhizzML developers, WhizzML’s power as a full-blown functional programming language can sometimes obscure the relationship between WhizzML and
