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.
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.
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.
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?
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.
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.
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
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.
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.
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.
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.
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