AI/ML

Backfilling integrates historical data into data pipelines, ensuring completeness and mitigating failures. Mage provides a no-code UI and custom coding options to streamline backfilling for robust, resilient data pipelines.

Accuracy tells overall correctness. Precision is specific to a category. Recall tells you successful detection of a specific category.

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.

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.

Create accurate predictions, eliminate guesswork, and create magical customer experiences with Mage.

Using machine learning and artificial intelligence to integrate product recommendations gives the most accurate predictions for successful advertising, eliminates guesswork in creating campaigns, and creates magical customer experiences. 

Using machine learning (ML) to battle “Nigerian princes,” hackers, and customers abusing chargeback requests in order to reduce unnecessary losses.

Creating measurable strategies to ensure customer retention, and taking data-driven actions to prevent churn, is key to thriving in the ever-growing, competitive ecommerce market.

Why aren’t prospects doing what we want? Figure out how we can use ML to show viewers what they’re searching for and get them to buy immediately.

Wall street banks use a variety of tools when making market predictions. One of those tools is machine learning software. Using Mage to build a model that can estimate next-day prices can be another asset for individuals wanting to make predictions.