Developers

Clean data sets the foundation for the success model to be built. Ensuring your AI/ML models are build with clean data can save time and money.

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.

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

In this blog, we’ll explore discrete and categorical features in the Telco Customer Churn dataset using univariate graphical methods.

A picture is worth a thousand words! Learn how to visualize the story told by your data.

Once you have a model, how do you know how well it works? Become Neo and enter the Matrix.

Learn how to import and export training models to share with the world!

Many invest heavily into remarketing strategies with vendors, but what about building your own? Leverage existing consumer data for your next campaign.

Apply feature engineering by converting time series data to numerical values for training machine learning models.

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.