Mage Blog

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.

As a step towards data processing, learn how to merge multiple datasets together and analyze the story behind the data.

The banking industry is an essential part of our finances. Those who adopt artificial intelligence will have a clear advantage for their future success.

Structure your interview process to emulate what it’s like to work together on your team and a typical day on the job.

Learn how to use AI to select your next outfit that matches the occasion. Featuring Pandas and the merge function to find all combinations.

We raised money. You might be thinking “so what, everyone else did as well”. I’ll try not to make this another fundraising announcement.

Before training ML models from multiple datasets, we need to understand how datasets work together. We’ll cover relationships in data using join and merge.