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HOPSWORKS

Python-centric Feature Store

Easily build and manage feature, training and inference pipelines. Support for Python, PySpark, Spark, Flink, and SQL.

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Integrate your Data platforms and ML platforms

Hopsworks is the most effective feature platform for designing and operating feature pipelines, training pipelines, and inference pipelines. Runs out of the box with your existing pipelines, so you don’t have to redesign your pipelines to work with Hopsworks.

Data Flow with a feature store

For all teams and all data

Increase team productivity and deploy your models faster.

Richard Woolston

"Our journey with Hopsworks has been an amazing transformation that's really enabled us to be innovative and reach a point that we wouldn't have been able to reach otherwise.”

Richard Woolston

Data Science Manager - AFCU

1000s of Users

Join the ever growing list of epic companies using Hopsworks.

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Jump right in

Our Python SDK is designed for ease of use. You simply import the Hopsworks library in your Python or PySpark program, connect to your project and start writing data to the feature store.

It is just as easy to create training data from selected features or get inference data for batch or online applications. 

Read our docs to find out more.

# connect to Hopsworks

import hopsworks

project = hopsworks.login()
fs = project.get_feature_store()
# create a feature group

transactions_dataframe = ...

transaction_fg
= fs.get_or_create_feature_group(    
   name="Transactions_30min_aggregates",
   version="1",
   description="Transaction fatures 30 mins window",
   primary_key=['cc_id'],
   event_time='datetime'
)

transaction_fg.insert(transactions_dataframe)

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