Codetown ::: a software developer's community
The Devoxx Poland call for papers closed!
es 3/31/16. Why should you submit your abstract? Devoxx Poland occurs in beautiful Krakow. June 22-24 are the dates. That's the most desirable time to be in central Europe. It's a global conference so you'll meet people from all over the world.
There were over 2000 participants last year. The…
ContinueAdded by Michael Levin on March 30, 2016 at 7:30am — No Comments
Oracle Academy’s free program offers learning resources and technologies for individual students:
BIG DATA ONLINE TRAINING
The objective of trainings, developed by Dan McClary, the product manager of “Oracle Academy Big Data Science…
ContinueAdded by Michael Levin on November 13, 2015 at 6:05pm — No Comments
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
Added by Carol McDonald on August 4, 2015 at 11:15am — No Comments
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,…
ContinueAdded by Carol McDonald on April 13, 2015 at 9:14am — 1 Comment
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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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Serving Large Language Models (LLMs) at scale is complex. Modern LLMs now exceed the memory and compute capacity of a single GPU or even a single multi-GPU node. As a result, inference workloads for 70B+, 120B+ parameter models, or pipelines with large context windows, require multi-node, distributed GPU deployments.
By Claudio Masolo
Karrot replaced its legacy recommendation system with a scalable architecture that leverages various AWS services. The company sought to address challenges related to tight coupling, limited scalability, and poor reliability in its previous solution, opting instead for a distributed, event-driven architecture built on top of scalable cloud services.
By Rafal Gancarz
Sharing your work as a software engineer inspires others, invites feedback, and fosters personal growth, Suhail Patel said at QCon London. Normalizing and owning incidents builds trust, and it supports understanding the complexities. AI enables automation but needs proper guidance, context, and security guardrails.
By Ben LindersThe article shares goals and strategies for scaling cloud and distributed applications, focusing on lessons learned from cloud migration at Chase.com at JP Morgan Chase. The discussion centers on three primary goals and the strategies addressing the goals, concluding how these approaches were achieved in practice. For those managing large-scale systems, these lessons provide valuable guidance!
By Durai Arasan
At the recent GitHub Universe 2025 developer conference, Arm unveiled the Cloud migration assistant custom agent, a tool designed to help developers automate, optimize, and accelerate the migration of their x86 cloud workflows to Arm infrastructure.
By Sergio De Simone
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