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Posted on August 4, 2015 at 11:15am 0 Comments 1 Like
This post discusses building a recommendation model from movie ratings using an iterative algorithm and parallel processing with Apache Spark MLlib.
https://dzone.com/links/parallel-and-iterative-processing-for-machine-lear.html
Posted on April 13, 2015 at 9:14am 1 Comment 0 Likes
Recommendation engines help narrow your choices to those that best meet your particular needs. In this post, we’re going to take a closer look at how all the different components of a recommendation engine work together. We’re going to use collaborative filtering on movie ratings data to recommend movies. The key components are a collaborative filtering algorithm in Apache Mahout to build and train a machine learning model,…
ContinuePosted on March 30, 2009 at 10:30am 0 Comments 0 Likes
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Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.
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Vercel has released Skills.sh, an open-source tool designed to provide AI agents with a standardized way to execute reusable actions, or skills, through the command line.
By Daniel Dominguez
Cursor has published Agent Trace, a draft open specification aimed at standardizing how AI-generated code is attributed in software projects. Released as a Request for Comments (RFC), the proposal defines a vendor-neutral format for recording AI contributions alongside human authorship in version-controlled codebases.
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As systems grow, observability becomes harder to maintain and incidents harder to diagnose. Agentic observability layers AI on existing tools, starting in read-only mode to detect anomalies and summarize issues. Over time, agents add context, correlate signals, and automate low-risk tasks. This approach frees engineers to focus on analysis and judgment.
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By Daniel Curtis
GitHub engineers recently traced user reports of unexpected “Too Many Requests” errors to abuse-mitigation rules that had accidentally remained active long after the incidents that prompted them.
By Matt Foster
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