Welcome to the feature store newsletter brought to you by Logical Clocks, where we in a monthly cadence will highlight the latest news, events, and insights as we help make companies successful in their machine learning transformation journey and empower businesses to be applied-AI model-driven companies. This month's edition highlights conferences in the Spark/AI Summit focused on feature stores.
Spark/AI Summit - Feature Store Talks
The next edition of Spark + AI Summit will be totally virtual and open to everyone. Below you will find presentations relating to feature stores. Note that there are now 5 talks on feature stores at this year’s conference - that is a 500% increase from last year!
Building a Feature Store around Dataframes and Apache Spark
Fabio Buso and Jim Dowling from Logical Clocks will talk about the Hopsworks Feature Store and how it integrates with Databricks. They will explain how the Hopsworks Feature Store centralises features for ML for easier discovery and governance, enables the reuse of features in different ML projects and provides a single pipeline or engineering features for both training and inference.
A Declarative Feature Engineering Framework
Nikhil Simha from AirBnB will talk about Zipline, their declarative feature engineering framework and Feature Store.
Orchestrating Spark ML Pipelines and MLflow for Production
Nathan Buesgens at Accenture is due to talk about orchestrating Spark ML Pipelines and MLflow for Production in a Feature Store - “ break the anti-pattern of ‘clone and own’ ML pipelines”.
Accelerate Real-Time ML with a Feature Platform
Mike Del Balso of Tacton.ai will talk about their Feature Store and its support for centralized management of features for serving and training along with version-control.
AI-Assisted Feature Selection for Big Data Modelling
Alvin Henrick from Clarify Health Solutions will talk about an AI assisted way to identify which features improve the accuracy of a model and by how much - using AI to help select the best features for your models.
Data Science Meetup Hamburg
When: May 28, 6:30 PM GMT+2
Speaker: Moritz Meister, Software Engineer at Logical Clocks AB
Topic: Feature Store: Filling the Gap in ML Infrastructure
ML Feature Stores: A Casual TourText
Moussa Taifi presents a thorough, well-researched 3-part introduction to Feature Stores (follow the links on this post to read each part).
Feature store: Solving anti-patterns in ML-systems
Andrzej Michałowski of Synerise gave a talk on Feature Stores at Big Data Warsaw in February 2020, where they use ClickHouse as the main data layer in their Feature Store. This is the first time we have seen ClickHouse appear as a database in a Feature Store - interesting!
Hopsworks.ai: First Cloud Native Feature Store
Logical Clocks released the first managed feature store platform for the cloud, hopsworks.ai, that is now available for early access on AWS. The Hopsworks Feature Store supports integration with Databricks, AWS Sagemaker, Hadoop platforms, and KubeFlow.
Tecton invests in AI data platform
Tecton has come out of stealth to announce they are building a managed feature store for ML. Tecton.ai was founded by members of the Michelangelo team at Uber, who built one of the industry’s first feature stores. They have raised in total a staggering $25m from investors such as Andreeson Horowitz and Sequoia Capital.
Twitter is looking for an engineering manager to head up their feature store, Cortex.
Hopsworks Feature Store for KubeFlow and On-Premises Clusters (Hadoop)
During this webinar we will introduce the concept of a Feature Store and how it helps manage data for AI. We will walk-through the Hopsworks Feature Store, introducing its concepts and how you can use it from Kubeflow and On-Premises Clusters (Hadoop) for feature engineering, as a feature registry, for creating train/test datasets for ML, and as an online Feature Store to build feature vectors for online applications with low latency.
Managed Feature Store for Machine Learning
Dr. Jim Dowling presents a webinar by Logical Clocks on Managed Feature Stores for ML: what are they, and why they are useful.
Hopsworks Store for SageMaker
Dr. Jim Dowling presents a webinar by Logical Clocks on Hopsworks Feature Stores integration with AWS SageMaker: why and how to integrate, with demo.
An Introduction to Machine Learning Feature Stores
Harmeet Sokhi presents a webinar by Thoughtworks on Feature Stores: what are they, and why they are useful.
Hopsworks - Data-Intensive AI with a Feature Store
Recording of a talk given at the Data Engineering Meetup in Melbourne on April 30th by Jim Dowling of Logical Clocks, with an end-to-end demo of Hopsworks.ai using the Feature Store