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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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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