Growth

We setup Hyperquery at Mage to organize and streamline our growth data for better insights. In this blog, we go over our experience of quickly adopting the tool and easily sharing our analysis with our peers.

Mage is an open-source data pipeline tool for transforming and integrating data. Find out how Mage compares to open-source ELT alternatives like Airbyte. We’ll break down the features, pricing, pros, cons, and more.

Partitioners of machine learning (ML) find data cleaning the #1 pain point, but are the current resources available enough to solve the problem? Join our discussion as we try to find out what data scientists need.

Is your model performing better than expected? Double-check if there’s data leakage that is inflating the accuracy and incorrectly evaluating your model performance!

In this Mage Academy lesson, we’ll be going over how to evaluate ranking models built for recommendation & personalization using mean average precision at K.

In this Mage Academy guide, we’ll go over how to evaluate a machine learning (ML) model and learn how to improve the model’s performance.

Channel your inner scholar and Ryze to the top – leverage machine learning ranking models that can increase your rank in League of Legends through match analysis and predictions, free of code!

In this Mage Academy lesson, we’ll build a model to classify the genre of a song based on the given attributes.

In this lesson from Mage Academy, we’ll look at one method of data cleaning, filter. Learn how to filter numbers, words, and just about anything in order to reduce bias in your dataset.

ML tools make it possible to predict and prevent churn before it occurs. Churn prediction is used to identify areas of improvement and maintain happy customers.