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Started Sep 18, 2009
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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
Codetown is a social network. It's got blogs, forums, groups, personal pages and more! You might think of Codetown as a funky camper van with lots of compartments for your stuff and a great multimedia system, too! Best of all, Codetown has room for all of your friends.
Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.
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The panelists discuss designing platform architecture where product, platform, and operations meet. Experts share best practices for reducing cognitive load, balancing core ops vs. innovation, measuring success (lead time, cost avoidance), and enabling developers through self-service and golden path deviations.
By Ran Isenberg, Garima Bajpai, Stephane DiCesare, Martin Reynolds, Faizan Panwala, Renato Losio
AWS has elevated Rust support in Lambda from experimental to generally available, empowering developers to create high-performance, memory-safe serverless applications. This milestone enhances developer confidence, backed by AWS support and SLA. While it offers speed comparable to C++, challenges such as lengthy SDK compile times and increased binary sizes remain key considerations.
By Steef-Jan Wiggers
Sustainable APIs benefit most from minimalism, Jochen Joswig said at OOP Conference . Deployment should consider energy, usage, carbon intensity, hardware acquisition. Remote work, long device lifespans, and green office practices can lower emissions. Efficient CI, selective builds, smaller artefacts, and optimized assets can further reduce energy use.
By Ben Linders
At QCon San Francisco, Netflix engineers unveiled their advanced Service-Level-Prioritized Load-Shedding strategy, enhancing reliability during traffic spikes. By prioritizing high-value requests and automating management across microservices, they safeguard user experience and system stability. Key insights stress prioritization, automation, and structured load shedding for optimal resilience.
By Steef-Jan Wiggers
Researchers at Microsoft, working in collaboration with Arizona State University, have introduced Magentic Marketplace, an open-source simulation environment designed to study how LLM-based agents behave in multi-agent economic systems. The platform addresses a growing need in AI research as autonomous agents gain capabilities in software development.
By Vinod Goje
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