Ensign

Have you ever tried to build a model that can handle new data in real time? We set out to do just that, and discovered that there aren’t a lot of tutorials about training real-time machine learning models, so we made this one!

Real-time data streams are powerful, but sometimes you need to convert the stream into a batch or replay parts of the stream. Here’s how to write customized SQL to more deeply understand and interact with your historic data.

With the rise of LLMs and Retrieval Augmented Generation (RAG), online models have never been more relevant. Here’s how to write some Python code to interpret real-time data and build your own adaptive online model.

One of the first steps in every data science or machine learning project is data ingestion. In this module, you will use Python to create a publisher to ingest real-time data into Ensign.

If you struggle to build analytics and models that keep up with changing data, it might be because you haven’t yet learned to think about data in terms of topics. In this module, learn how by solving a real-world, real-time problem!

The Python SDK is the most popular way to use Ensign. In this module you will write some Python code to publish data to your project.

Welcome to PubSub 101! In this module you will create a new Ensign account and a new project. After completing this module, you will have an API key that you can use to publish data to Ensign!

A new SEC proposal will make publicly traded orgs disclose ESG data like environmental impacts and workforce stats. Many anticipate challenges to compliance, but a new approach to data synthesis is here to help.