This guide introduces you to a suite of classification performance metrics in Python and some visualization methods that every data scientist should know.
Data scientists need to have a good understanding of how to select the best features when it comes to model building. This guide will help you get started.
Whether you’re brand new to machine learning or have tried (and failed) to get models working in Python, Weka may be the perfect starting point for you.
To make the most of machine learning for their clients, data scientists need to be able to explain the likely factors behind a model's predictions. Python offers multiple ways to do just that.
It’s cutting-edge now, but soon a data fabric will be an essential tool. Here’s how it will transform data architecture and create a new competitive advantage.
By leveraging natural language processing, augmented analytics could revolutionize the way data science teams — and non-specialist business users — get the information their firms need.
