Evaluation Store + Feature Store

Miles is a Partner Sales Engineer at Snowflake and leads the technical go-to-market  and joint product integration strategy for Snowflake's machine learning and data science partners. Miles has spent the entirety of his career in data science and sales engineering positions and specializes in financial markets and technology industries. With the rise of data platforms that now can enable data sharing, and the ability for feature stores to create data pipelines as code, the direction is clear that the "Feature Cloud" concept is heading towards us rapidly. What will this mean for data providers in how they structure and make their data available? Where in the stack will be the processes that manage data provider SLAs. Who will vote on changes to feature definitions? These are just some of the questions that we will need to answer for shared data to power production machine learning use cases. Want to see more about how Feast and Snowflake play well together? Check out this blog post. If you would like to share your story with us about how you are using Feast, get in touch! For more info about feature stores check out the Tecton blog or have a look at the Feast website Join the Tecton/Feast slack channel to speak with like-minded engineers. Connect with Willem on LinkedIn Connect with Miles on LinkedIn Connect with Demetrios on LinkedIn Follow Feast on Twitter Check out Tecton on Twitter

Danny Chiao is an engineering lead at Tecton/Feast Inc working on building a next-generation feature store. Previously, Danny was a technical lead at Google working on end to end machine learning problems within Google Workspace, helping build privacy-aware ML platforms / data pipelines and working with research and product teams to deliver large-scale ML powered enterprise functionality. Danny holds a Bachelor’s degree in Computer Science from MIT. In this session Danny tells Demetrios Brinkmann from the MLOps Community how he works with the Feast Community to drive design decisions. He gives some hot takes on how working at Google is much different than working for a startup, especially in the Machine Learning and Feature Store space.  The current Python Centric Feast meets you where you are, whether thats a small team of 2 data scientists, or a platform team at Twitter. The Feast ecosystem is built with scalability and performance capabilities in mind. Danny was conscientious about how with the Python centric Feast approach it is not throwing the kitchen sink at uses from the start. The idea now is to allow teams to add as much complexity as needed once up and running with Feast. If you would like to share your story with us about how you are using Feast, get in touch! For more info about feature stores check out the Tecton blog or have a look at the Feast website Join the Tecton/Feast slack channel to speak with like-minded engineers. Connect with Demetrios On LinkedIn Connect with Danny on LinkedIn Follow Feast on Twitter Check out Tecton on Twitter

Aparna Dhinakaran spoke with Demetrios and Willem about the 3 tools you need to do ML - an evaluation store, a feature store and a model store. Before getting into the full conversation about the integration between Feast and Arize AI, the team talked about what exactly an evaluation store is and why its needed. Aparna's article about the three tools you need to do ML - https://towardsdatascience.com/the-only-3-ml-tools-you-need-1aa750778d33 The Feast and Arize integration blog - https://arize.com/feast-and-arize-supercharge-feature-management-and-model-monitoring-for-mlops/ If you would like to share your story with us about how you are using Feast, get in touch! For more info about feature stores check out the Tecton blog or have a look at the Feast website Join the Tecton/Feast slack channel to speak with like-minded engineers. Connect with Aparna on LinkedIn or Twitter Connect with WIllem On LinkedIn Connect with Demetrios On LinkedIn Follow Feast on Twitter Check out Tecton on Twitter

In this episode Jay Parthasarthy sat down to talk with Demetrios Brinkmann about the vision for Feast and what a Product Manager does for the Feast ecosystem.  If you would like to share your story with us about how you are using Feast, get in touch! For more info about feature stores check out the Tecton blog or have a look at the Feast website Join the Tecton/Feast slack channel to speak with like-minded engineers. Connect with Jay on LinkedIn or Twitter Connect with Demetrios On LinkedIn Follow Feast on Twitter Check out Tecton on Twitter

Oleksii Moskalenko joins Demetrios Brinkmann to talk about how the team at Gojek is using Feast. Some of the main work Oleksii is doing is on the platform team. This episode centers around what his team focuses on when enabling data scientist, and what some of the main use ML cases are at Gojek. Oleksii is currently an Engineering Lead at Gojek's Data Science Platform, leading the Feature Store development. Prior to that he was Algorithm Engineer working on productionizing deep learning (computational photography) models at Wix. Moskalenko's main focus is helping to convert academia's accomplishments in Data Science into industrial software solving real-world problems.  Overall he has 15 years experience in software engineering with the last 6 years focusing on Data Engineering & productionizing Machine Learning. If you would like to share your story with us about how you are using Feast, get in touch! For more info about feature stores check out the Tecton blog or have a look at the Feast website Join the Tecton/Feast slack channel to speak with like-minded engineers. Connect with Demetrios On LinkedIn Connect with Oleksii On Linkedin Follow Feast on Twitter Check out Tecton on Twitter

David Aronchick has worked for tech giants such as Microsoft, Amazon and Google. He is most notably known for his role in creating the open source ML tool Kubeflow. Yes Kubeflow. In this conversation Willem, Demetrios and David talk about challenges the current MLOps ecosystem faces, where the market is going and the Feast + Kubeflow dynamics.  If you would like to share your story with us about how you are using Feast, get in touch! For more info about feature stores check out the Tecton blog or have a look at the Feast website Join the Tecton/Feast slack channel to speak with like-minded engineers. Connect with David On LinkedIn or twitter Connect with WIllem On LinkedIn Connect with Demetrios On LinkedIn Follow Feast on Twitter Check out Tecton on Twitter

Feast creator Willem Pinaar and MLOps community organizer Demetrios Brinkmann are joined in this episode by Joost Rothweiler of Adyen. The episode dives into their on-prem use case and how the MLOps platform team at Adyen decided on using Feast for their feature store. Bio: Joost Rothweiler leads the machine learning platform team at Adyen. His team is concerned with helping data scientists in the organization deliver value from machine learning by enabling them to iterate quickly and release new models with confidence. Joost has been involved with building out the machine learning infrastructure from the beginning and is especially motivated to drive the democratization of the use of machine learning in the broader organization. In the last months, the focus has been on delivering a feature store to provide consistent access to training and serving data, with the aim to create more powerful models and drive operational excellence. If you would like to share your story with us about how you are using Feast, get in touch! For more info about feature stores check out the Tecton blog or have a look at the Feast website Join the Tecton/Feast slack channel to speak with like-minded engineers.  Connect with Joost On LinkedIn Connect with WIllem On LinkedIn Connect with Demetrios On LinkedIn Follow Feast on Twitter Check out Tecton on Twitter

Matt Ziegler is a lead software engineer at online retailer Zulily, where he works on the machine learning, data science and martech teams to create personalized shopping experiences at scale for millions of customers around the world. Passionate about open source and problem solving, Matt contributes to Feast after more than a decade of experience in software development. Notable projects include leading the expansion of the machine learning platform and leading containerization and Docker orchestration at Zulily, where he arrived after leading several teams at McKesson. Matt graduated from the University of Idaho with dual degrees in computer science and business information systems, and when not at work, enjoys spending time with his family in Washington state. In this episode, Willem, Matt and Demetrios talk about some of the key factors Zulily considered while bringing on the feature store Feast.  If you would like to share your story with us about how you are using Feast, feel free to get in touch and we will make it happen. For more info about feature stores check out the Tecton blog Or have a look at the Feast website Connect with Matt On LinkedIn Connect with WIllem On LinkedIn Connect with Demetrios On LinkedIn Follow Feast on Twitter Check out Tecton on Twitter Have a look at Zulily

In the first episode of this series revolving around insights related to the Open Source Feature Store Feast, Demetrios and Willem sit down to talk about the journey thus far. What is the back story around this open source feature store. If you would like to share your story with us about how you are using Feast, feel free to get in touch and we will make it happen. For more info about feature stores check out the Tecton blog Or have a look at the Feast website Connect with WIllem Pinaar On LinkedIn Connect with Demetrios On LinkedIn Follow Feast on Twitter Check out Tecton on Twitter