Our upcoming webinar:

Coming soon

Model Monitoring with KFServing and Hopsworks

Watch this webinar to learn how we integrate the KubeFlow Model Serving (KFServing) with the Hopsworks Feature Store, logging prediction requests on KFServing in Kafka and processing them with Spark before storing them in the Hopsworks Feature Store for analysis.

MLOps + Feature Store

Watch this webinar to learn how the Hopsworks Feature Store enables MLOps workflows for training models using features from the Feature Store, analyzing and validating models, deploying them into online model serving infrastructure, and monitoring model performance in production.

Real-time Predictions with a Feature Store

Watch this webinar to learn 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.

Data Governance with the Hopsworks Feature Store

Watch this webinar to learn about the best practices for securing and governing your data assets for machine learning. We discuss how to solve security and governance problems for machine learning pipelines with the Feature Store.

Feature Engineering with Hopsworks Feature Store

Watch this webinar to learn how a feature store factors monolithic end-to-end ML pipelines into feature engineering and model training pipelines that can each run at different cadences. In particular, we take a look at the input to the Hopsworks Feature Store: the feature engineering pipelines.

Hopsworks Feature Store on Microsoft Azure

Watch this video to learn how to manage features for training and serving models in a cluster under your control inside your Azure account. From within Hopsworks or on Azure Databricks or Azure ML Studio, you can explore and inspect available features as well as create training data in a file format of your choice

Solve Fraud Challenges with Graph Network and Deep Learning in Hopsworks

Watch this video to learn how deep learning (both supervised & unsupervised learning) and graph network can increase anomaly detection rates and reduce costs associated with fraud and anti-money laundering.

Hopsworks.AI - A feature Store for Machine Learning

Watch our presentation at PyData Amsterdam 2020 to learn how we built the world’s first managed feature store for the cloud, hopsworks.ai.

Time Travel and Provenance for Machine Learning Pipelines

Watch this video to learn what "implicit provenance" for ML is, how we added support in , and how it helps with debugging and governing ML pipelines.

Manage your own Feature Store on Databricks with Hopsworks

Watch this demo to learn how to engineer your features on Databricks and publish them to Hopsworks Feature Store.

Feature Engineering with a Cloud-Native Feature Store with Hopsworks

Learn in depth about the benefits of a feature store to manage data for artificial intelligence and how you can use it as a managed platform on AWS.

Building a Feature Store around Dataframes and Apache Spark

We introduce Maggy, an open source platform that provides a new way of writing machine learning applications that reduce the burden on data scientists becoming distributed systems experts.

From Python to PySpark and Back Again Unifying Single host and Distributed Deep Learning with Maggy

We introduce an open-source framework Maggy that enables write-once training functions that can be reused in single-host Python programs and cluster-scale PySpark programs.

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

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

This webinar covers the main principles of a Feature Store, Hopsworks Feature Store and how it can be integrated with Amazon SageMaker with a short demonstration.

Managed Feature Store
for Machine Learning

During this video we explain in more detail the concept of a Feature Store. We show how the Feature Store can help manage feature data for Enterprises and ease the path of data from back-end systems and data-lakes to Data Scientists. We also go through our take on Feature Stores, including best practices

Hopsworks Feature Store integration for Databricks

In this webinar we cover the main principle of a Feature Store, what is Hopsworks Feature store and how it can be integrated with Databricks for feature engineering as a feature registry to create  train/test datasets for ML and to build feature vectors for online applications with low latency.

Hopsworks Feature Store for managing ML feature data

This webinar is about our take on Feature Stores, including best practices, use cases and how to ensure Consistent Features in both Training and Serving, Governance, Access-Control, and Versioning, Unified Online and Offline Storage- Feature Data Validation and much more!

Feature Engineering with Hopsworks Feature Store

Watch this webinar to learn how a feature store factors monolithic end-to-end ML pipelines into feature engineering and model training pipelines that can each run at different cadences. In particular, we take a look at the input to the Hopsworks Feature Store: the feature engineering pipelines.

Hopsworks Feature Store on Microsoft Azure

Watch this video to learn how to manage features for training and serving models in a cluster under your control inside your Azure account. From within Hopsworks or on Azure Databricks or Azure ML Studio, you can explore and inspect available features as well as create training data in a file format of your choice

Solve Fraud Challenges with Graph Network and Deep Learning in Hopsworks

Watch this video to learn how deep learning (both supervised & unsupervised learning) and graph network can increase anomaly detection rates and reduce costs associated with fraud and anti-money laundering.

Hopsworks.AI - A feature Store for Machine Learning

Watch our presentation at PyData Amsterdam 2020 to learn how we built the world’s first managed feature store for the cloud, hopsworks.ai.

Time Travel and Provenance for Machine Learning Pipelines

Watch this video to learn what "implicit provenance" for ML is, how we added support in , and how it helps with debugging and governing ML pipelines.

Manage your own Feature Store on Databricks with Hopsworks

Watch this demo to learn how to engineer your features on Databricks and publish them to Hopsworks Feature Store.

Feature Engineering with a Cloud-Native Feature Store with Hopsworks

Learn in depth about the benefits of a feature store to manage data for artificial intelligence and how you can use it as a managed platform on AWS.

Building a Feature Store around Dataframes and Apache Spark

We introduce Maggy, an open source platform that provides a new way of writing machine learning applications that reduce the burden on data scientists becoming distributed systems experts.

From Python to PySpark and Back Again Unifying Single host and Distributed Deep Learning with Maggy

We introduce an open-source framework Maggy that enables write-once training functions that can be reused in single-host Python programs and cluster-scale PySpark programs.

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

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

This webinar covers the main principles of a Feature Store, Hopsworks Feature Store and how it can be integrated with Amazon SageMaker with a short demonstration.

Managed Feature Store
for Machine Learning

During this video we explain in more detail the concept of a Feature Store. We show how the Feature Store can help manage feature data for Enterprises and ease the path of data from back-end systems and data-lakes to Data Scientists. We also go through our take on Feature Stores, including best practices

Hopsworks Feature Store integration for Databricks

In this webinar we cover the main principle of a Feature Store, what is Hopsworks Feature store and how it can be integrated with Databricks for feature engineering as a feature registry to create  train/test datasets for ML and to build feature vectors for online applications with low latency.

Hopsworks Feature Store for managing ML feature data

This webinar is about our take on Feature Stores, including best practices, use cases and how to ensure Consistent Features in both Training and Serving, Governance, Access-Control, and Versioning, Unified Online and Offline Storage- Feature Data Validation and much more!

Our upcoming webinar:

Coming soon

Time Travel and Provenance for Machine Learning Pipelines

Watch this video to learn what "implicit provenance" for ML is, how we added support in , and how it helps with debugging and governing ML pipelines.

Manage your own Feature Store on Databricks with Hopsworks

Watch this demo to learn how to engineer your features on Databricks and publish them to Hopsworks Feature Store.

Feature Engineering with a Cloud-Native Feature Store with Hopsworks

Learn in depth about the benefits of a feature store to manage data for artificial intelligence and how you can use it as a managed platform on AWS.

Building a Feature Store around Dataframes and Apache Spark

We introduce Maggy, an open source platform that provides a new way of writing machine learning applications that reduce the burden on data scientists becoming distributed systems experts.

From Python to PySpark and Back Again Unifying Single host and Distributed Deep Learning with Maggy

We introduce an open-source framework Maggy that enables write-once training functions that can be reused in single-host Python programs and cluster-scale PySpark programs.

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

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

This webinar covers the main principles of a Feature Store, Hopsworks Feature Store and how it can be integrated with Amazon SageMaker with a short demonstration.

Managed Feature Store
for Machine Learning

During this video we explain in more detail the concept of a Feature Store. We show how the Feature Store can help manage feature data for Enterprises and ease the path of data from back-end systems and data-lakes to Data Scientists. We also go through our take on Feature Stores, including best practices

Hopsworks Feature Store integration for Databricks

In this webinar we cover the main principle of a Feature Store, what is Hopsworks Feature store and how it can be integrated with Databricks for feature engineering as a feature registry to create  train/test datasets for ML and to build feature vectors for online applications with low latency.

Hopsworks Feature Store for managing ML feature data

This webinar is about our take on Feature Stores, including best practices, use cases and how to ensure Consistent Features in both Training and Serving, Governance, Access-Control, and Versioning, Unified Online and Offline Storage- Feature Data Validation and much more!

Our upcoming webinar:

Coming soon