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Real-Time Predictions with a Feature Store

This video shows how you can leverage the Hopsworks online feature store to compute and ingest features and make them available to operational models making real-time predictions, with low latency and preventing skew between the training and serving features.

Simplifying Feature Engineering with a Feature Store

A feature store is a data platform that manages and governs your features for machine learning - both for training and serving. You have access to and can reuse previously engineered features available within the entire organisation, avoiding the need to write a feature engineering pipeline for every model put in production.

Hopsworks Feature Store with Microsoft Azure

The Hopsworks Feature Store is available today on Azure as both a managed platform (www.hopsworks.ai) and a custom Enterprise installation. It manages your features for training and serving models in a cluster under your control inside your organisation’s existing cloud account.

Solve Fraud Challenges with Graph Network and Deep Learning in Hopsworks

Financial institutions invest huge amounts of resources in both identifying and preventing money laundering and fraud. Most existing systems for identifying money laundering are rules-based that are not capable of detecting ever changing schemes. Consequently, these systems generate too many false-positive alerts, taking time and money to run down.

Feature Engineering with a Cloud-Native Feature Store with Hopsworks.ai

The Hopsworks.ai is the world's first managed feature store for the cloud that provides an open-source and general purpose feature store to design and operate AI applications at scale with Apache Spark.

Hopsworks Feature Store for Kubeflow and On-Premises Clusters (Hadoop)

The Hopsworks Feature Store is a platform for managing and serving features for machine learning that also integrates Kubeflow and On-Premises Clusters (Hadoop).

Hopsworks Feature Store for SageMaker

The Hopsworks Feature Store is a platform for managing and serving features for machine learning. It integrates seamlessly with popular platforms for Data Science and cloud-based data lakes based on S3.

Managed Feature Store

All hyperscale AI companies (LinkedIn, Facebook, AiBnB, Microsoft, Google, etc) build their machine learning platforms around a Feature Store.