Remove Algorithm Remove Apache Kafka Remove Events
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Streaming Machine Learning Without a Data Lake

ODSC - Open Data Science

Be sure to check out his talk, “ Apache Kafka for Real-Time Machine Learning Without a Data Lake ,” there! The combination of data streaming and machine learning (ML) enables you to build one scalable, reliable, but also simple infrastructure for all machine learning tasks using the Apache Kafka ecosystem.

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Real-time artificial intelligence and event processing  

IBM Journey to AI blog

By leveraging AI for real-time event processing, businesses can connect the dots between disparate events to detect and respond to new trends, threats and opportunities. AI and event processing: a two-way street An event-driven architecture is essential for accelerating the speed of business.

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Memphis: A game changer in the world of traditional messaging systems

Data Science Dojo

Challenges for individuals Traditional messaging brokers, such as Apache Kafka, RabbitMQ, and ActiveMQ, have been widely used to enable communication between applications and services. Handling too many data sources can become overwhelming, especially with complex schemas. Debugging and troubleshooting can also be challenging.

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Big Data – Lambda or Kappa Architecture?

Data Science Blog

In this representation, there is a separate store for events within the speed layer and another store for data loaded during batch processing. It is important to note that in the Lambda architecture, the serving layer can be omitted, allowing batch processing and event streaming to remain separate entities.

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Big data engineering simplified: Exploring roles of distributed systems

Data Science Dojo

Different algorithms and techniques are employed to achieve eventual consistency. Unlike traditional batch processing, where data is processed in fixed intervals, stream processing enables organizations to gain insights and respond to events as they happen in real-time. They use redundancy and replication to ensure data availability.

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Bundesliga Match Facts Shot Speed – Who fires the hardest shots in the Bundesliga?

AWS Machine Learning Blog

This process comprises two key components: event data and optical tracking data. Event data collection entails gathering the fundamental building blocks of the game. For the precision needed in shot speed calculations, we must ensure that the ball’s position aligns precisely with the moment of the event.

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Five scalability pitfalls to avoid with your Kafka application

IBM Journey to AI blog

Apache Kafka is a high-performance, highly scalable event streaming platform. To unlock Kafka’s full potential, you need to carefully consider the design of your application. It’s all too easy to write Kafka applications that perform poorly or eventually hit a scalability brick wall.