Mage Blog

Artificial Intelligence is shifting recruiting from a human to largely computer-based process — from curating job descriptions to conducting interviews.

When collecting consumer data, there are times when you’re unable to retrieve all the data so you’ll want to “guestimate” what the data should be.

Machines have an easy time understanding numbers, but can't comprehend meaning. Learn techniques to scale numerical data to better grasp your data.

With the evolution of AI comes many tools for product developers. AI isn’t replacing your job, it’s making it easier and here’s how.

Technical design documents are detailed game plans for features or solutions to technical problems. They end up saving your team a lot of time and code.

The future of business means AI. Onboarding talent capable of collecting data via machine learning is expensive but essential to stay relevant.

Machines have a hard time understanding data humans can read. Apply encoding on qualitative data to train models more efficiently.

A machine learning (ML) project requires collaboration across many roles. Here are high level steps in the end-to-end ML lifecycle for each role they play.

Fueled by an increase in online shopping, e-commerce platforms have been utilizing AI to improve experience and optimize their business performance.

A process to create, review, and merge pull requests is a must when working as a team. Communication and collaboration effectively gets the job done.