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  • Big Data Processing Using Apache Spark - Part 6: Graph Data Analytics with Spark GraphX

    by Srini Penchikala on  Mar 14, 2017 1

    In this article, author Srini Penchikala discusses Apache Spark GraphX library used for graph data processing and analytics. The article includes sample code for graph algorithms like PageRank, Connected Components and Triangle Counting.

  • Data Preprocessing vs. Data Wrangling in Machine Learning Projects

    by Kai Wähner on  Mar 05, 2017

    This article compares different alternative techniques to prepare data, including extract-transform-load (ETL) batch processing, streaming ingestion and data wrangling. The article also discusses how this is related to visual analytics, and best practices for how different user roles such as the Data Scientist or Business Analyst should work together to build analytic models.

  • Article Series: An Introduction to Machine Learning

    by Michael Manapat on  Feb 27, 2017

    In this series, we give an introduction to some powerful but generally applicable techniques in machine learning. These include deep learning but also more traditional methods that are often all the modern business needs. After reading the articles in the series, you should have the knowledge necessary to embark on concrete machine learning experiments in a variety of areas on your own.

Book Review: Andrew McAfee and Erik Brynjolfsson's "The Second Machine Age"

Posted by Michael Manapat on  Feb 24, 2017

Andrew McAffee and Erik Brynjolfsson begin their book The Second Machine Age with a simple question: what innovation has had the greatest impact on human history?

Real-World, Man-Machine Algorithms

Posted by Edwin Chen Justin Palmer on  Feb 16, 2017

Learn about the end-to-end flow of developing machine learning models: where you get training data, how you pick the ML algorithm, what you must address after your model is deployed, and so forth.

Anomaly Detection for Time Series Data with Deep Learning

Posted by Tom Hanlon on  Feb 11, 2017

This article introduces neural networks, including descriptions of feed-forward and recurrent neural networks, describing how to build a recurrent neural network that detects anomalies.

An Introduction to Differential Privacy

Posted by Charlie Cabot on  Jan 22, 2017

Differential privacy leapt from research papers to tech news headlines last year when, in the WWDC keynote, Apple VP of Engineering Craig Federighi announced Apple’s use of the concept in iOS. 1

Peter Cnudde on How Yahoo Uses Hadoop, Deep Learning and Big Data Platform

Posted by Srini Penchikala on  Oct 13, 2016

Yahoo uses Hadoop for different use cases in big data & machine learning areas. InfoQ spoke with Peter Cnudde on how Yahoo leverages big data technologies.

Spark GraphX in Action Book Review and Interview

Posted by Srini Penchikala on  Sep 12, 2016

InfoQ spoke with authors of Spark GraphX in Action book, Apache Spark framework and what's coming up in the area of graph data processing and analytics.

Big Data Processing with Apache Spark - Part 4: Spark Machine Learning

Posted by Srini Penchikala on  May 15, 2016

In this fourth installment of Apache Spark article series, author Srini Penchikala discusses machine learning concept & Spark MLlib library for running predictive analytics using a sample application.

Spark in Action Book Review & Interview

Posted by Srini Penchikala on  Mar 18, 2016

In Spark in Action book, authors Petar and Marko discuss Apache Spark for data processing batch & streaming data. InfoQ spoke with them about Spark framework, developer tools, and upcoming features.

Will AI Surpass Human Intelligence? Interview with Prof. Jürgen Schmidhuber on Deep Learning

Posted by Han Xu on  Mar 08, 2016

People worry about whether AI will surpass human intelligence these days. Prof. Juergen Schmidhuber will answer your questions and tell you more about deep learning as well as the latest trends in AI. 5

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