Go SDK to interact with the Hopsworks API

Serverless Machine Learning for Titanic Dataset

The work uses Hopsworks for Feature store and creating Feature groups for Machine learning modeling

A study project to explore Hopsworks - a fraud detection classifier. The project was inspired by one of the tutorials available in the Hopsworks documentation.

Building a full cycle of Machine learning Prediction App for Air quality

shows how to backfill Energy Consumption feature in a Feature Store (Hopsworks) using an orchestration tool (Prefect).

FastRide: NYC Taxi Trip Duration Prediction employs machine learning techniques to accurately predict the duration of taxi trips in New York City, helping transportation businesses optimize operations and enhance customer satisfaction.

Forecasting Ethereum return quantiles using a handful of different statistical learning models and selecting the best based on out of sample error. Hopsworks feature store and model registry is used to automate the process. Ethereum quantile returns are predicted daily and displayed on a Streamlit dashboard.

This is a batch-inference service of NYC Taxi rides 🚗.

Predicting Snow Conditions in Passo Tonale (Trento, Italy)

Terraform module that creates the required cloud resources for Hopsworks.ai clusters on AWS and AZURE.

Backfill historical OHLC feature in a Feature Store (Hopsworks) using an orchestration tool (Prefect).

Hopsworks.ai Terraform provider

A simple app to help you find relevant machine learning papers to read.

Learn to build a modular real-time feature pipeline, so you avoid Offline-Online Feature Skew, and your deployed ML models work as expected.

Python - Java/Scala API for the Hopsworks feature store

Develop and deploy a real-time feature pipeline in Python, using Bytewax 🐝 and Hopsworks Feature Store.

Compute and store real-time features for crypto trading using Bytwax (stream processing) and Hopsworks (Feature Store)

A project to deploy an online app that predicts the win probability for each NBA game every day. Demonstrates end-to-end Machine Learning deployment.