We are bringing you the latest news from Hopsworks!
We are pleased to bring back our new newsletter, focused on updates and insights into our feature store solution, Hopsworks.
We aim to keep you up-to-date with the latest advancements and improvements, including new features, performance improvements, and bug fixes. We will also share insights from our engineering team and industry experts on best practices for feature engineering, machine learning, and no infra MLOps.
At Hopsworks, we are committed to providing our users with the best possible experience; this newsletter is one way we strive to achieve that. We look forward to sharing our updates with you and continuing to support your data science efforts.
??Updates
Hopsworks 3.1 is out!
This version includes features store improvements (time-series splits for training data, support for managing thousands of models), stability, and user-interface improvements.
Hopsworks 3.2 is coming up soon and includes new capabilities in automated feature monitoring and faster features through the offline API using a new experimental service based on DuckDB and Arrow Flight Service, which we call Flying Duck.
Status Page
We are introducing our new status page for hopsworks.ai! Stay informed and up-to-date on any service interruptions or maintenance with real-time updates.
?? Cool Projects using Hopsworks
Predicting Likes On Reddit
This is an ML project to predict the number of likes a Reddit post/comment is expected to get if the user decides to post it. The project is built using Hopsworks and Modal.
Predicting the Tesla Stock Market
This is an ML project that predicts the Tesla stock price. It uses time-series data for training an LSTM model. The project is built using Hopsworks and Modal.
?? Read, learn, work
Optimize your MLOps Workflow with a Feature Store CI/CD and Github Actions
Learn how to set up a workflow (using Github Actions) to validate, test and deploy the pipeline code on Hopsworks.
Testing feature logic, transformations, and feature pipelines with pytest
We show you how to design, build, and run offline tests for features with pytest and the Hopsworks feature store.
Feature Types for Machine Learning
We define a feature type and discuss what a feature type means in the context of the Hopsworks Feature Store.
?? Community
Hopsworks, Medborgarplatsen 25, Stockholm, Stockholms l?n 118 26, Sweden