Learn more about how feature stores are evolving to be the engine for RAG and MCP servers and how you can build real-time AI systems.

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In this webinar, we’ll showcase how Brewer enables domain experts to build and iterate on AI pipelines—without writing brittle glue code or managing complex orchestration logic.

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Maximize GPU efficiency with Hopsworks on Kubernetes—optimize scheduling, sharing, and tracking for scalable, cost-effective AI workloads.

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Unlock real-time fraud detection with rolling aggregations, enabling faster, more accurate AI-driven prevention at scale.

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Empowering government and law enforcement with secure, AI-driven solutions to enhance efficiency, security, and citizen services.

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Build scalable, real-time recommendation systems that power personalized experiences across e-commerce, streaming, and social platforms.

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How to make LLMs aware of non-verbal actions (clicks, orders, etc) in applications.

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Explore how AI is transforming retail with Hopsworks, enabling personalization, efficiency, resilience, and advanced data governance.

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Discover how you can get DeepSeek models up and running in an on-premises or cloud-based Kubernetes cluster in minutes with Hopsworks.

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Learn how Hopsworks Medical Copilot supports healthcare professionals throughout the treatment lifecycle, ensuring that no information is overlooked and allowing providers to dedicate more quality time to delivering improved patient care.

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Hear from top AI experts and industry leaders as they explore the current state of AI in the Nordics, discussing practical applications, trends and more.

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Discover the AI Lakehouse - advancing real-time data and Python support for batch, real-time, and LLM AI systems.

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Join us to learn how Hopsworks powers Agile Copilot for developers, scrum masters, project managers, and teams.

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Hopswork's chatbot that predicts diagnoses from chest X-rays using MONAI Toolkit’s TransCheX model.

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In this webinar we will demonstrate how the new AI regulation requirements can drive efficiency and productivity in AI teams.

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In this webinar, we will show you how to build and operate a real-time feature streaming pipeline that writes at 1m ops/sec - TikTok Scale.

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We'll examine the architectural nuances of Redis and RonDB, shedding light on key factors such as data persistence, scalability, and transaction support.

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Build a LLM that detects whether a scanned image of a cheque is a fraud.

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Explore the synergies between ML Platforms and Graph Algorithms.

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Let's build an AI system that allows you to search your private PDF files.

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This live session will look into extending RAG for LLMs to include the ability to query structured data and API calls using function calling.

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In this live coding session, we'll explore creating sub-second fresh feature pipelines, retrieving low-latency features, and on-demand feature computation on Hopsworks, along with other capabilities.

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Explore Hopsworks' High Availability capabilities, showcasing the resilience of individual components and a multi-region architecture.

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In this webinar, we show how to build from scratch an entire machine learning application that can go into production in 3 weeks.

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In this webinar, we show how to build from scratch an entire machine learning application that can go into production in 3 weeks.

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In this webinar, we show how to build from scratch an entire machine learning application that can go into production in 3 weeks.

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In this webinar, we show how to build from scratch an entire machine learning application that can go into production in 3 weeks.

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In this webinar, we show how to build from scratch an entire machine learning application that can go into production in 3 weeks.

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In this webinar, we show how to build from scratch an entire machine learning application that can go into production in 3 weeks.

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In this webinar, we will see the 3 programs you need to write to productionize a fine-tuned RAG LLM.

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In this webinar, we show how to build an entire machine learning application from scratch that can go into production in 3 weeks and meet the stringent response time and availability of SLAs at extreme scale.

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In this webinar, we show how to build an entire machine learning application from scratch that can go into production in 3 weeks and meet the stringent response time and availability of SLAs at extreme scale.

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In this webinar, we show how to build an entire machine learning application from scratch that can go into production in 3 weeks and meet the stringent response time and availability of SLAs at extreme scale.

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Monitoring features for ML models is something that generally is overlooked when monitoring models in production. In this webinar we will demonstrate how observe and monitor features in Hopsworks for a more holistic approach to model monitoring.

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In today's competitive market, customer relationship management is crucial for businesses to thrive. In this webinar we will show you how to use Hopsworks for building and deploying machine learning models for CRM.

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Money laundering is a significant threat towards organizations facing increasing pressure to detect and prevent financial crimes. In this webinar we will show you how to build and deploy AML models using Hopsworks.

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Credit risk is a crucial aspect in the financial industry, with organizations continuously seeking ways to improve their credit risk models. Delve into the entire life cycle of building and deploying credit risk models using Hopsworks.

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Identity resolution is a critical task in many industries. Join us as we walk through the entire life cycle of building and deploying fraud detection models using Hopsworks and open-source foundation models.

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Fraud prevention is a crucial aspect in many industries, from banking and finance to e-commerce and insurance. Join us as we walk through the entire life cycle of building and deploying fraud detection models using Hopsworks.

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In this webinar, we will walk through the LLM life cycle on Hopsworks and show you how to build LLM applications on your private data with Hopsworks and open-source foundation models.

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Explore the AI landscape in the Nordics and uncover the true business value of AI.

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In this webinar, we will introduce the "feature view" from Hopsworks, which is the API for ML model development.

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In this webinar, we will analyze the synergies of an integrated Feature Store and Model Serving platform for the operationalization of real-time ML-enabled services.

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In this webinar, we will introduce the challenges of building online feature pipelines, including integration with a feature store, online model serving infrastructure, and real-time feature computation, with stream processing and on-demand features.

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In this talk we will discuss how Hopsworks can be connected to existing cloud native data warehouses like Snowflake, Redshift and BigQuery.

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In this webinar we will explain the core concepts of great expectations and how we made them available on Hopsworks to be used within your feature pipelines. Users are able to define expectation suites or reuse their existing ones.

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Training an ML model nowadays is the easy part — managing the lifecycle of the experiments and the model is where things get complicated.

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In this webinar, Fabio Buso, VP of Engineering at Hopsworks will present the new 3.0 release; How our new Feature View and write APIs have evolved to help Data Scientists bring their models to production, and other state-of-the art new improvements.

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Join us to learn how performance at any scale is impacted by high availability infrastructures, and how those capabilities impact the value that is generated from the use of machine learning.

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Join us to learn how a feature store, with its multiple data sources and diversity of connectors, streaming data, and online data sets, allows teams to work together, share information, and complement each other's work.

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The modern data team consists of Data Engineers, Data Scientists, Machine Learning Engineers, and Business Analysts, but effective collaboration is challenging. In this talk we will show how a centralized data platform helps solve these issues.

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Learn how to install and configure Hopsworks on your local machines, and how to connect to the Hopsworks Feature Store.

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Learn how to build and operate search and recommendation systems on Hopsworks, with support for the most important pieces of infrastructure.

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Learn how to develop and deploy online models at ease for the open-source KServe and Hopsworks platforms without extensive MLOPs experience.

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A live walk through on how to work with features, both offline and online. We will have a live coding demo on how to get started with Hopsworks, create features and push them to the Hopsworks Feature Store.

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