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Source channel @githubtrending · Post #15132 · Sep 10

#scala X's Recommendation Algorithm uses machine learning to show you posts and content you are most likely to engage with across its platform, including the "For You" timeline and notifications. It gathers a large pool of posts from people you follow and others you might like, then ranks them by predicting your interest based on your past actions like likes, clicks, and replies. It also filters out unwanted content and mixes in sponsored posts to keep your feed relevant and diverse. This means your feed is personalized to show you the most interesting and safe content, improving your experience on X. https://github.com/twitter/the-algorithm

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djangoproject

@djangoproject · Post #519 · 12/10/2017, 06:14 PM

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https://blog.wallaroolabs.com/2017/12/stateful-multi-stream-processing-in-python-with-wallaroo/ #Wallaroo is a high-performance, open-source framework for building distributed stateful applications. In an earlier post, we looked at how Wallaroo scales #distributed_state. In this post, we’re going to see how you can use Wallaroo to implement multiple data processing #tasks performed over the same shared #state. We’ll be implementing an application we’ll call “Market Spread” that keeps track of the latest pricing information by stock while simultaneously using that state to determine whether stock order #requests should be rejected. #pipeline

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