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Title & Speakers	Event
Building Machine Learning Systems with a Feature Store 2025-11-07 Jim Dowling – author Get up to speed on a new unified approach to building machine learning (ML) systems with a feature store. Using this practical book, data scientists and ML engineers will learn in detail how to develop and operate batch, real-time, and agentic ML systems. Author Jim Dowling introduces fundamental principles and practices for developing, testing, and operating ML and AI systems at scale. You'll see how any AI system can be decomposed into independent feature, training, and inference pipelines connected by a shared data layer. Through example ML systems, you'll tackle the hardest part of ML systems--the data, learning how to transform data into features and embeddings, and how to design a data model for AI. Develop batch ML systems at any scale Develop real-time ML systems by shifting left or shifting right feature computation Develop agentic ML systems that use LLMs, tools, and retrieval-augmented generation Understand and apply MLOps principles when developing and operating ML systems data ai-ml machine-learning AI/ML Data Modelling LLM MLOps RAG	O'Reilly AI & ML Books
LLMOps with Hopsworks and Modal Labs 🧪 2024-05-08 · 22:30 Join PyData NYC at 11 Times Square (Microsoft) on May 8th at 6:30 pm for a talk night with Jim Dowling (CEO of Hopsworks) and Eric Bernhardsson (CEO of Modal Labs). Please bring your 💻 to code along and sign up with your government official name! 🍕 Pizza, drinks & venue sponsored by Microsoft Reactor - thank you! Agenda: Modular AI Systems with Feature, Training, Inference Pipelines on Hopsworks - a LLMOps Tutorial Speaker: Jim Dowling In this tutorial, we will introduce a unified architecture for Batch, Real-Time, and LLM AI Systems based around three independent ML pipelines - * a feature pipeline to create feature data, * a training pipeline to train your model, * and an inference pipeline to make predictions with new data on your trained model. We will use this FTI architecture to walk through a tutorial of building a LLM system that uses RAG and function calling to access structured data and a model. Jim Dowling is CEO of Hopsworks and an Associate Professor at KTH Royal Institute of Technology. He is lead architect of the open-source Hopsworks Feature Store platform and the organizer of the annual feature store summit. He is writing a book for O'Reilly on Building AI systems with a Feature Store - batch, real-time, and LLMs. Introduction to Modal Speaker: Erik Bernhardsson Modal's platform empowers data/AI/ML teams to develop faster at lower cost, while scaling production workloads to thousands of CPUs and GPUs. Networking Connect with fellow data enthusiasts, professionals, and community leaders. Build meaningful connections and forge collaborations. ---------------------------------------------------------------- RSVP is required; please note that walk-ins will not be accepted. Note: Per building policy, RSVPs will close at 12 pm on May 6th. Doors @ 6 pm Event @ 6:30 - 8:30 pm Venue provided by MSFT: 11 Times Square ---------------------------------------------------------------- The building requires a government-issued photo ID for entrance. This, and all PyData NYC events, is an all-level event. Newcomers and beginners are welcome. This, and all NumFOCUS-affiliated events and spaces, both in-person and online, are governed by a Code of Conduct. ---------------------------------------------------------------- This event may be recorded.	LLMOps with Hopsworks and Modal Labs 🧪
PyData NYC: LLMOps with Hopsworks and Modal Labs 🧪 2024-05-08 · 22:30 NYC Python will be joining PyData NYC at 11 Times Square (Microsoft) on on May 8th at 6:30 pm for a talk night with Jim Dowling (CEO of Hopsworks) and Eric Bernhardsson (CEO of Modal Labs). Please bring your 💻 to code along and sign up with your government official name! 🏢 Venue sponsored by Microsoft Reactor - thank you ⚠️Please RSVP with PyData NYC here: https://www.meetup.com/pydatanyc/events/300430791/ Agenda: Modular AI Systems with Feature, Training, Inference Pipelines on Hopsworks - a LLMOps Tutorial Speaker: Jim Dowling In this tutorial, we will introduce a unified architecture for Batch, Real-Time, and LLM AI Systems based around three independent ML pipelines - * a feature pipeline to create feature data, * a training pipeline to train your model, * and an inference pipeline to make predictions with new data on your trained model. We will use this FTI architecture to walk through a tutorial of building a LLM system that uses RAG and function calling to access structured data and a model. Jim Dowling is CEO of Hopsworks and an Associate Professor at KTH Royal Institute of Technology. He is lead architect of the open-source Hopsworks Feature Store platform and the organizer of the annual feature store summit. He is writing a book for O'Reilly on Building AI systems with a Feature Store - batch, real-time, and LLMs. Introduction to Modal Speaker: Eric Bernhardsson Modal's platform empowers data/AI/ML teams to develop faster at lower cost, while scaling production workloads to thousands of CPUs and GPUs. Networking Connect with fellow data enthusiasts, professionals, and community leaders. Build meaningful connections and forge collaborations. ---------------------------------------------------------------- RSVP is required; please note that walk-ins will not be accepted. Note: Per building policy, RSVPs will close at 12 pm on May 6th. Doors @ 6 pm Event @ 6:30 - 8:30 pm Venue provided by MSFT: 11 Times Square ---------------------------------------------------------------- The building requires a government-issued photo ID for entrance. This, and all PyData NYC events, is an all-level event. Newcomers and beginners are welcome. This, and all NumFOCUS-affiliated events and spaces, both in-person and online, are governed by a Code of Conduct. ---------------------------------------------------------------- This event may be recorded.	PyData NYC: LLMOps with Hopsworks and Modal Labs 🧪
Exploring the Power of LLMs and Generative AI 2023-08-24 · 15:30 Welcome to another PyData Stockholm meetup! 🌟 We're thrilled to kick off our post-summer meetup with a special focus on Large Language Models (LLMs) hosted by Google Cloud. Large Language Models (LLMs) have created a significant buzz in the AI community, captivating researchers and industry professionals alike. LLMs have the ability to generate highly coherent and contextually relevant text in response to a prompt (or query), sparking immense excitement and exploration in various applications, ranging from content generation to virtual assistants. In this meetup, we will have two talks that will give insights to LLMs in general and how to personalize LLMs with a feature store. You'll also learn about Google's advancements in developing LLMs and how they can be harnessed by consumers and enterprises alike. Join us for an exciting event featuring two thought-provoking talks on Large Language Models (LLMs) and their applications! 👉 RSVP: Register here! 👈 ❗Please note that you will need to register through the above link in order to confirm your seat at the event. Agenda 17:30 - 18:00: Doors open 18:00 - 18:10: Welcome 18:10 - 18:40: Personalized LLMs with a Feature Store 18:40 - 19:10: Pizza & Beers 19:10 - 19:40: Large Language models and Generative AI at Google 19:40 - 21:00: Networking --- Presentations Personalized LLMs with a Feature Store Jim Dowling - CEO & Co-Founder, Hopsworks Large Language Models (LLMs) provide a model of the world, through a model of language. In this talk, we will walk through how to personalize a LLM using prompt-engineering with a feature store. The feature store will provide personalized history and context information for LLMs. Speaker Bio: Jim Dowling is CEO of Hopsworks and an Associate Professor at KTH Royal Institute of Technology. He is lead architect of the open-source Hopsworks Feature Store platform. He is the organizer of the annual Feature Store Summit and the Feature Store for ML community at featurestore.org. Large Language models and Generative AI at Google Zoe Tang - Customer Engineer / GenAI Specialist, Google Cloud Sweden Zoe will talk about Google's journey in developing Large Language Models and what is offered to consumers and enterprises. How large language models can be used in multiple modalities and solve different types of problems. And how they can be used in Google Cloud. Speaker Bio: Zoe is an AI + Cloud enthusiast who believes by heart that AI and ML can fundamentally change the way we live. She has 10+ years experience in the IT industry and works at Google Cloud as GenAI Specialist, primarily focusing on GenAI engagements for Sweden and Nordics customers. In her daily work, she meets with organizations to discuss how GenAI can be implemented to help them accelerate their business. --- About the event Date: August 24th, 17:30 - 21:00 Location: Google’s Office - Kungsbron 2, 111 22 Stockholm Directions: 5-7 minutes walk from T-Centralen or Hötorget stations. Tickets: Sign up required. Anyone who is not on the list will not get in. Capacity: Space is limited to 90 participants. If you are signed up but unable to attend, please let us know. Food and drinks: Pizza and drinks will be provided Questions: Please contact the meetup organizers. --- Code of Conduct The NumFOCUS Code of Conduct applies to this event; please familiarize yourself with it before attending. If you have any questions or concerns regarding the Code of Conduct, please contact the organizers.	Exploring the Power of LLMs and Generative AI
PyData Berlin 2023 August Meetup 2023-08-16 · 16:00 Welcome to the next Pydata Berlin meetup !! We would like to welcome you all starting at 18:00. The talks begin around 18:30. Please provide your first and last name for the registration because this is required for the venue's entry policy. If you cannot attend, please cancel your spot so others are able to join as the space is limited. ************************************************************************ The Lineup for the Evening Talk 1: Cohort Revenue & Retention Analysis: A Bayesian Approach Speaker: Juan Camilo Orduzs a Mathematician (Ph.D. Humboldt Universität zu Berlin) and data scientist at Wolt. He is interested in interdisciplinary applications of mathematical methods. In particular, time series analysis, bayesian methods, and causal inference. Abstract: We present a Bayesian approach to model cohort-level retention rates and revenue over time. We use Bayesian additive regression trees (BART) to model the retention component which we couple with a linear model to model the revenue component. This method is flexible enough to allow adding additional covariates to both model components. This Bayesian model allows us to quantify the uncertainty in the estimation, understand the effect of the covariates on the retention through partial dependence plots (PDP), individual conditional expectation (ICE) plots and last but not least forecast the future revenue, and retention rates. Talk 2: The Mythical Machine Learning Pipeline Speaker: Jim Dowling is CEO of Hopsworks and an Associate Professor at KTH Royal Institute of Technology. He is lead architect of the open-source Hopsworks Feature Store platform. He organizes the annual feature store summit and co-organizes PyData Stockholm. Abstract: Developers often talk about ML pipelines as a concrete building block for production ML systems. However, these monolithic creatures are almost never seen in production. Instead, real-world ML systems are typically factored into manageable pipelines with dedicated tasks. In this talk, we show how to build ML systems as a composition of feature pipelines, training pipelines, and inference pipelines with a shared data layer. There will be slots for 2-3 Lightning Talks (5-6 Minutes for each). Kindly let us know if you would like to present something at the start of the meetup :) * NumFOCUS Code of Conduct THE SHORT VERSION Be kind to others. Do not insult or put down others. Behave professionally. Remember that harassment and sexist, racist, or exclusionary jokes are not appropriate for NumFOCUS. All communication should be appropriate for a professional audience including people of many different backgrounds. Sexual language and imagery are not appropriate. NumFOCUS is dedicated to providing a harassment-free community for everyone, regardless of gender, sexual orientation, gender identity, and expression, disability, physical appearance, body size, race, or religion. We do not tolerate harassment of community members in any form. Thank you for helping make this a welcoming, friendly community for all. If you haven't yet, please read the detailed version here: https://numfocus.org/code-of-conduct * HOSTS**: Spiced Academy: Accelerate your career with our first-class bootcamps in Web Development, Data Science, Data Analytics and UX/UI.	PyData Berlin 2023 August Meetup

Building Machine Learning Systems with a Feature Store 2025-11-07

Jim Dowling – author

Get up to speed on a new unified approach to building machine learning (ML) systems with a feature store. Using this practical book, data scientists and ML engineers will learn in detail how to develop and operate batch, real-time, and agentic ML systems. Author Jim Dowling introduces fundamental principles and practices for developing, testing, and operating ML and AI systems at scale. You'll see how any AI system can be decomposed into independent feature, training, and inference pipelines connected by a shared data layer. Through example ML systems, you'll tackle the hardest part of ML systems--the data, learning how to transform data into features and embeddings, and how to design a data model for AI. Develop batch ML systems at any scale Develop real-time ML systems by shifting left or shifting right feature computation Develop agentic ML systems that use LLMs, tools, and retrieval-augmented generation Understand and apply MLOps principles when developing and operating ML systems

data ai-ml machine-learning AI/ML Data Modelling LLM MLOps RAG

O'Reilly AI & ML Books

LLMOps with Hopsworks and Modal Labs 🧪 2024-05-08 · 22:30

Join PyData NYC at 11 Times Square (Microsoft) on May 8th at 6:30 pm for a talk night with Jim Dowling (CEO of Hopsworks) and Eric Bernhardsson (CEO of Modal Labs). Please bring your 💻 to code along and sign up with your government official name!

🍕 Pizza, drinks & venue sponsored by Microsoft Reactor - thank you!

Agenda: Modular AI Systems with Feature, Training, Inference Pipelines on Hopsworks - a LLMOps Tutorial Speaker: Jim Dowling In this tutorial, we will introduce a unified architecture for Batch, Real-Time, and LLM AI Systems based around three independent ML pipelines - * a feature pipeline to create feature data, * a training pipeline to train your model, * and an inference pipeline to make predictions with new data on your trained model. We will use this FTI architecture to walk through a tutorial of building a LLM system that uses RAG and function calling to access structured data and a model.

Jim Dowling is CEO of Hopsworks and an Associate Professor at KTH Royal Institute of Technology. He is lead architect of the open-source Hopsworks Feature Store platform and the organizer of the annual feature store summit. He is writing a book for O'Reilly on Building AI systems with a Feature Store - batch, real-time, and LLMs.

Introduction to Modal Speaker: Erik Bernhardsson Modal's platform empowers data/AI/ML teams to develop faster at lower cost, while scaling production workloads to thousands of CPUs and GPUs.

Networking Connect with fellow data enthusiasts, professionals, and community leaders. Build meaningful connections and forge collaborations.

---------------------------------------------------------------- RSVP is required; please note that walk-ins will not be accepted. Note: Per building policy, RSVPs will close at 12 pm on May 6th. Doors @ 6 pm Event @ 6:30 - 8:30 pm Venue provided by MSFT: 11 Times Square ---------------------------------------------------------------- The building requires a government-issued photo ID for entrance. This, and all PyData NYC events, is an all-level event. Newcomers and beginners are welcome. This, and all NumFOCUS-affiliated events and spaces, both in-person and online, are governed by a Code of Conduct. ---------------------------------------------------------------- This event may be recorded.

LLMOps with Hopsworks and Modal Labs 🧪

PyData NYC: LLMOps with Hopsworks and Modal Labs 🧪 2024-05-08 · 22:30

NYC Python will be joining PyData NYC at 11 Times Square (Microsoft) on on May 8th at 6:30 pm for a talk night with Jim Dowling (CEO of Hopsworks) and Eric Bernhardsson (CEO of Modal Labs). Please bring your 💻 to code along and sign up with your government official name! 🏢 Venue sponsored by Microsoft Reactor - thank you

⚠️Please RSVP with PyData NYC here: https://www.meetup.com/pydatanyc/events/300430791/

Agenda: Modular AI Systems with Feature, Training, Inference Pipelines on Hopsworks - a LLMOps Tutorial Speaker: Jim Dowling In this tutorial, we will introduce a unified architecture for Batch, Real-Time, and LLM AI Systems based around three independent ML pipelines - * a feature pipeline to create feature data, * a training pipeline to train your model, * and an inference pipeline to make predictions with new data on your trained model. We will use this FTI architecture to walk through a tutorial of building a LLM system that uses RAG and function calling to access structured data and a model. Jim Dowling is CEO of Hopsworks and an Associate Professor at KTH Royal Institute of Technology. He is lead architect of the open-source Hopsworks Feature Store platform and the organizer of the annual feature store summit. He is writing a book for O'Reilly on Building AI systems with a Feature Store - batch, real-time, and LLMs. Introduction to Modal Speaker: Eric Bernhardsson Modal's platform empowers data/AI/ML teams to develop faster at lower cost, while scaling production workloads to thousands of CPUs and GPUs. Networking Connect with fellow data enthusiasts, professionals, and community leaders. Build meaningful connections and forge collaborations. ---------------------------------------------------------------- RSVP is required; please note that walk-ins will not be accepted. Note: Per building policy, RSVPs will close at 12 pm on May 6th. Doors @ 6 pm Event @ 6:30 - 8:30 pm Venue provided by MSFT: 11 Times Square ---------------------------------------------------------------- The building requires a government-issued photo ID for entrance. This, and all PyData NYC events, is an all-level event. Newcomers and beginners are welcome. This, and all NumFOCUS-affiliated events and spaces, both in-person and online, are governed by a Code of Conduct. ---------------------------------------------------------------- This event may be recorded.

PyData NYC: LLMOps with Hopsworks and Modal Labs 🧪

Exploring the Power of LLMs and Generative AI 2023-08-24 · 15:30

Welcome to another PyData Stockholm meetup! 🌟

We're thrilled to kick off our post-summer meetup with a special focus on Large Language Models (LLMs) hosted by Google Cloud.

Large Language Models (LLMs) have created a significant buzz in the AI community, captivating researchers and industry professionals alike. LLMs have the ability to generate highly coherent and contextually relevant text in response to a prompt (or query), sparking immense excitement and exploration in various applications, ranging from content generation to virtual assistants.

In this meetup, we will have two talks that will give insights to LLMs in general and how to personalize LLMs with a feature store. You'll also learn about Google's advancements in developing LLMs and how they can be harnessed by consumers and enterprises alike.

Join us for an exciting event featuring two thought-provoking talks on Large Language Models (LLMs) and their applications!

👉 RSVP: Register here! 👈

❗Please note that you will need to register through the above link in order to confirm your seat at the event.

Agenda 17:30 - 18:00: Doors open 18:00 - 18:10: Welcome 18:10 - 18:40: Personalized LLMs with a Feature Store 18:40 - 19:10: Pizza & Beers 19:10 - 19:40: Large Language models and Generative AI at Google 19:40 - 21:00: Networking --- Presentations Personalized LLMs with a Feature Store Jim Dowling - CEO & Co-Founder, Hopsworks Large Language Models (LLMs) provide a model of the world, through a model of language. In this talk, we will walk through how to personalize a LLM using prompt-engineering with a feature store. The feature store will provide personalized history and context information for LLMs. Speaker Bio: Jim Dowling is CEO of Hopsworks and an Associate Professor at KTH Royal Institute of Technology. He is lead architect of the open-source Hopsworks Feature Store platform. He is the organizer of the annual Feature Store Summit and the Feature Store for ML community at featurestore.org.

Large Language models and Generative AI at Google Zoe Tang - Customer Engineer / GenAI Specialist, Google Cloud Sweden Zoe will talk about Google's journey in developing Large Language Models and what is offered to consumers and enterprises. How large language models can be used in multiple modalities and solve different types of problems. And how they can be used in Google Cloud. Speaker Bio: Zoe is an AI + Cloud enthusiast who believes by heart that AI and ML can fundamentally change the way we live. She has 10+ years experience in the IT industry and works at Google Cloud as GenAI Specialist, primarily focusing on GenAI engagements for Sweden and Nordics customers. In her daily work, she meets with organizations to discuss how GenAI can be implemented to help them accelerate their business. --- About the event Date: August 24th, 17:30 - 21:00 Location: Google’s Office - Kungsbron 2, 111 22 Stockholm Directions: 5-7 minutes walk from T-Centralen or Hötorget stations. Tickets: Sign up required. Anyone who is not on the list will not get in. Capacity: Space is limited to 90 participants. If you are signed up but unable to attend, please let us know. Food and drinks: Pizza and drinks will be provided Questions: Please contact the meetup organizers. --- Code of Conduct The NumFOCUS Code of Conduct applies to this event; please familiarize yourself with it before attending. If you have any questions or concerns regarding the Code of Conduct, please contact the organizers.

Exploring the Power of LLMs and Generative AI

PyData Berlin 2023 August Meetup 2023-08-16 · 16:00

Welcome to the next Pydata Berlin meetup !!

We would like to welcome you all starting at 18:00. The talks begin around 18:30.

Please provide your first and last name for the registration because this is required for the venue's entry policy. If you cannot attend, please cancel your spot so others are able to join as the space is limited.

************************************************************************** The Lineup for the Evening

Talk 1: Cohort Revenue & Retention Analysis: A Bayesian Approach

Speaker: Juan Camilo Orduzs a Mathematician (Ph.D. Humboldt Universität zu Berlin) and data scientist at Wolt. He is interested in interdisciplinary applications of mathematical methods. In particular, time series analysis, bayesian methods, and causal inference.

Abstract: We present a Bayesian approach to model cohort-level retention rates and revenue over time. We use Bayesian additive regression trees (BART) to model the retention component which we couple with a linear model to model the revenue component. This method is flexible enough to allow adding additional covariates to both model components. This Bayesian model allows us to quantify the uncertainty in the estimation, understand the effect of the covariates on the retention through partial dependence plots (PDP), individual conditional expectation (ICE) plots and last but not least forecast the future revenue, and retention rates.

Talk 2: The Mythical Machine Learning Pipeline

Speaker: Jim Dowling is CEO of Hopsworks and an Associate Professor at KTH Royal Institute of Technology. He is lead architect of the open-source Hopsworks Feature Store platform. He organizes the annual feature store summit and co-organizes PyData Stockholm.

Abstract: Developers often talk about ML pipelines as a concrete building block for production ML systems. However, these monolithic creatures are almost never seen in production. Instead, real-world ML systems are typically factored into manageable pipelines with dedicated tasks. In this talk, we show how to build ML systems as a composition of feature pipelines, training pipelines, and inference pipelines with a shared data layer.

There will be slots for 2-3 Lightning Talks (5-6 Minutes for each). Kindly let us know if you would like to present something at the start of the meetup :)

*** NumFOCUS Code of Conduct THE SHORT VERSION Be kind to others. Do not insult or put down others. Behave professionally. Remember that harassment and sexist, racist, or exclusionary jokes are not appropriate for NumFOCUS. All communication should be appropriate for a professional audience including people of many different backgrounds. Sexual language and imagery are not appropriate. NumFOCUS is dedicated to providing a harassment-free community for everyone, regardless of gender, sexual orientation, gender identity, and expression, disability, physical appearance, body size, race, or religion. We do not tolerate harassment of community members in any form. Thank you for helping make this a welcoming, friendly community for all. If you haven't yet, please read the detailed version here: https://numfocus.org/code-of-conduct *** HOSTS: Spiced Academy: Accelerate your career with our first-class bootcamps in Web Development, Data Science, Data Analytics and UX/UI.

PyData Berlin 2023 August Meetup

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