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ljvmiranda921.github.io | ||
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www.altexsoft.com
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| | | | | A dive into the machine learning pipeline on the production stage: the description of architecture, tools, and general flow of the model deployment. | |
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hypernephelist.com
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| | | | | In a recent project, we worked with our customer on a sustainability project whose goal was to leverage geospatial and climate data to build a platform to pe... | |
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dagshub.com
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| | | | | Explore the top ML workflow and pipeline tools, including tools from Netflix, to enhance your data science projects' efficiency and impact. | |
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jack-vanlightly.com
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| | | Over the past few months, I've seen a growing number of posts on social media promoting the idea of a "zero-copy" integration between Apache Kafka and Apache Iceberg. The idea is that Kafka topics could live directly as Iceberg tables. On the surface it sounds efficient: one copy of the data, unified access for both streaming and analytics. But from a systems point of view, I think this is the wrong direction for the Apache Kafka project. In this post, I'll explain why. | ||
