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All Blog Posts Tagged 'big' (4)
Devoxx Poland
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
BIG DATA ONLINE TRAINING for Student Developers!
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
movie recommendations with Spark machine learning
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
Added by Carol McDonald on August 4, 2015 at 11:15am — No Comments
An Inside Look at the Components of a Recommendation Engine
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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Welcome to Codetown!
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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InfoQ Reading List
Researchers Attempt to Uncover the Origins of Creativity in Diffusion Models
In a recent paper, Stanford researchers Mason Kamb and Surya Ganguli proposed a mechanism that could underlie the creativity of diffusion models. The mathematical model they developed suggests that this creativity is a deterministic consequence of how those models use the denoising process to generate images.
By Sergio De SimoneAtlassian's 4 Million PostgreSQL Database Migration: When Standard Cloud Strategies Fail
Atlassian recently migrated 4 million Jira databases to Amazon Aurora, intending to reduce costs and improve the reliability of its Jira Cloud platform. Due to the large number of files involved and the constraints of managed services, the team developed a custom tool to orchestrate the process, as traditional cloud migration strategies were not viable.
By Renato LosioLM Studio 0.3.17 Adds Model Context Protocol (MCP) Support for Tool-Integrated LLMs
LM Studio has released version 0.3.17, introducing support for the Model Context Protocol (MCP) — a step forward in enabling language models to access external tools and data sources. Originally developed by Anthropic, MCP defines a standardized interface for connecting LLMs to services such as GitHub, Notion, or Stripe, enabling more powerful, contextual reasoning.
By Robert KrzaczyńskiGrafana Tempo 2.8 Released: Major TraceQL Enhancements and Memory Optimizations
Grafana released Tempo 2.8 on June 12, 2025, introducing substantial memory optimizations and expanded functionality in its trace query language, TraceQL. This update is part of an ongoing effort to make distributed tracing more performant and accessible within observability stacks.
By Craig RisiGemma 3n Introduces Novel Techniques for Enhanced Mobile AI Inference
Launched in early preview last May, Gemma 3n is now officially available. It targets mobile-first, on-device AI applications, using new techniques designed to increase efficiency and improve performance, such as per-layer embeddings and transformer nesting.
By Sergio De Simone
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