H2O can get you to a similar end, though it is a much different tool — more similar to Scikit-learn, SparkML, or packages of choice from Github.

Monument is strictly no-code and everything is “batteries included” — a much lower hurdle for enterprise-grade analysis than firing up a code development…

COVID has dramatically altered all of our lives. The corresponding flurry of information — and sometimes misinformation — has made these changes more acute and harder to unpack.

To empower citizens, journalists, and policymakers, Monument has assembled below easy-to-follow instructions for building your own machine learning models for COVID’s spread…

NEW YORK, N.Y. — Monument is pleased to announce the roll out of “model serving” capabilities. Model serving enables users to train algorithms on historical data, save the parameterized model, and deploy this model on new data that the model has not previously seen.

Model serving complements the “training” and…

Stop putting prices on things by guessing. You’re leaving money on the table. A great use-case for Machine Learning is building pricing engines. No coding or data science expertise required.

Whether you’re buying or selling a product — any product! — it’s helpful to use Machine Learning to get a…

NEW YORK, N.Y. — The Monument team is pleased to announce the addition of classification and regression methods into our zero-code machine intelligence platform. Users can now estimate any types of classes or levels for your data. Monument will automatically adjust to your data set.

These classification and regression algorithms…

In this tutorial, we’re going to show you how to take open source data from the National Oceanic and Atmospheric Administration (NOAA), clean it, and forecast future temperatures using no-code machine learning methods.

This particular data comes from the Harmful Algal BloomS Observation System (HABSOS). There are several interesting questions…

Monument

Predictions to keep you two steps ahead.

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