Developers

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.

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

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

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

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

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.

In AI, it’s common to combine data; especially when training models. We’ll cover how to look at relationships when combining dataframes with concat.

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