InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
-
Facebook Open-Sources Deep Learning Project Torchnet
Facebook Artificial Intelligence Research laboratory open-sources the Torchnet project to package and optimize boiler plate deep learning code for reuse and plugin-ability.
-
QCon San Francisco 2016 Trackhosts Confirmed
QCon San Francisco, the largest English speaking conference organized by InfoQ, returns to the Bay Area November 7-9 for its tenth successive year. There are 18 tracks at QCon San Francisco, each an individually curated full-day vertical conference focused on important topics for software developers.
-
Meson Workflow Orchestration and Scheduling Framework for Netflix Recommendations
Netflix's goal is to predict what you want to watch before you watch it. They do this by running a number of machine learning (ML) workflows every day. Meson is a workflow orchestration and scheduling framework that manages the lifecycle of all these machine learning pipelines that build, train and validate personalization algorithms to help with the video recommendations.
-
QCon San Francisco 2016 Tracks Announced and First Glimpse at Workshops
QCon San Francisco, the 10th annual bay area software conference that attracts attendees from all over the world, returns to the Fishermen's Wharf area of San Francisco November 7-9, 2016.
-
Vert.x 3.3.0 Features Enhanced Networking Microservices, Testing and More
Vert.x core developer Clement Escoffier of RedHat explores key features of just released Vert.x 3.3.0 reactive toolkit.
-
Apache TinkerPop Graduates to Top-Level Project
TinkerPop, a graph compute framework for OLTP and OLAP graph database and analytics processing graduated to top-level project with the Apache Software Foundation.
-
Test Well and Prosper: The Great Java Unit-Testing Frameworks Debate
A recent post in Reddit sparked a debate between the traditional testing framework JUnit and upstart Spock with the central theme, “What’s wrong with JUnit?”
-
Neha Narkhede: Large-Scale Stream Processing with Apache Kafka
In her presentation "Large-Scale Stream Processing with Apache Kafka" at QCon New York 2016, Neha Narkhede introduces Kafka Streams, a new feature of Kafka for processing streaming data. According to Narkhede stream processing has become popular because unbounded datasets can be found in many places. It is no longer a niche problem like, for example, machine learning.
-
LinkedIn Details Production Kafka Debugging and Best Practices
LinkedIn’s Joel Koshy details their Kafka usage, debugging and monitoring two production incidents in using the core Kafka infrastructure concepts, semantics and behavioral patterns to plan for and detect similar problems in the future.
-
Data Streaming Architecture with Apache Flink
Jamie Grier recently spoke at OSCON 2016 Conference about data streaming architecture using Apache Flink. He talked about the building blocks of data streaming applications and stateful stream processing with code examples of Flink applications and monitoring.
-
LinkedIn Details Open-Sourced Kafka Monitor
LinkedIn recently detailed open-sourced Kafka Monitor service that they're using to monitor production Kafka clusters as well as extensive testing automation, leading them to identify bugs in the main Kafka trunk and contribute solutions to the open-source community.
-
Spring Releases Version 1.1 Statemachine Framework
Spring releases version 1.1 of their state machine framework, dubbed Statemachine, featuring support for Spring Security, built-in support for Redis, and support for UI modeling.
-
Confluent Platform 3.0 Supports Kafka Streams for Real-Time Data Processing
Confluent Platform 3.0 messaging system from Confluent, the company behind Apache Kafka messaging framework, supports Kafka Streams for real-time data processing. The company announced last week the general availability of the latest version of the open source Confluent platform.
-
Combine SQL Server with Hadoop Using PolyBase
With the recently released SQL Server 2016, you can now use SQL queries against Hadoop and Azure blob storage. Not only do you no longer need to write map/reduce operations, you can also join relational and non-relational data with a single query.
-
Cloudera Announces Partnership with the Broad Institute
Cloudera announced their partnership with MIT & Harvard's Broad Institute and detailed some of their experience with the Genome Analytics Toolkit pipeline.