Carol McDonald
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  • Jacksonville, Florida
  • United States
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What are your main interests in software development?
Java, Web, Ajax, Java EE, Spring, Seam, JPA, Web Services
Do you have a website?
http://weblogs.java.net/blog/caroljmcdonald/
Anything else you'd like to add? Where do you live? (optional!)
Je parle Francais. Ich kann Deutsch.

Carol McDonald's Blog

movie recommendations with Spark machine learning

Posted on August 4, 2015 at 11:15am 0 Comments

Tutorial on Apache Spark, movie recommendations with machine learning 

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

An Inside Look at the Components of a Recommendation Engine

Posted on April 13, 2015 at 9:14am 1 Comment

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,…

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screencast about MySQL for Developers

Posted on March 30, 2009 at 10:30am 0 Comments

Here is a screencast about MySQL for Developers



If you are a developer using MySQL, you should learn enough to take advantage of its strengths, because having an understanding of the database can help you develop better-performing applications. This session will talk about MySQL database design and SQL tuning for developers. Some topics include:



* MySQL Storage Engine Architecture

* Schema, the basic foundation of performance

* Think about performance when… Continue

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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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InfoQ Reading List

Anthropic Introduces MCP Tunnels for Private Agent Access to Internal Systems

Anthropic has expanded its Claude Managed Agents platform with two enterprise-focused capabilities: self-hosted sandboxes and MCP tunnels. The release aims to address a recurring challenge in enterprise AI deployments, where organizations want to use autonomous agents but cannot allow execution environments or internal systems to leave their security perimeter.

By Robert Krzaczyński

Agoda Builds Multimodal Content System to Bridge Images and Reviews in Travel Discovery

Agoda Multimodal Content Systemhttps://example.com/agoda-multimodal-content-systemAgoda unifies hotel images and guest reviews using a shared topic taxonomy, enabling multimodal retrieval across 700M+ images and multilingual reviews with offline enrichment and low-latency serving.

By Leela Kumili

Presentation: Powering the Future: Building Your GenAI Infrastructure Stack

Merrin Kurian shares the architectural blueprints and organizational processes behind Intuit’s AI transformation. She explains the "fixed, flexible, free" framework used to scale GenOS across 8,000 developers, enabling 3,500+ production experiments. She discusses critical agent failure modes, the "LLM-as-a-judge" evaluation strategy, and how to build "tool-ready" APIs for the future.

By Merrin Kurian

TanStack Details Sophisticated npm Supply Chain Attack That Compromised 42 Packages

TanStack has released a detailed postmortem describing a sophisticated supply-chain attack that compromised 42 npm packages and published 84 malicious package versions in just six minutes, exposing developers and CI/CD systems to credential theft and malware propagation.

By Craig Risi

Article: Kernel-Level Ground Truth: Why eBPF is Replacing User-Space Agents for Security Observability

eBPF is emerging as a preferred method for security observability over traditional user-space agents. By attaching probes directly to the Linux kernel's syscall interface, it provides consistent visibility even during container-level compromises. eBPF reduces security-related CPU consumption and limits data volume by performing filtering at the kernel level, enhancing operational efficiency.

By Niranjan Sharma

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