In this fourth installment of Apache Spark article series, author Srini Penchikala discusses machine learning concepts and Spark MLlib library for running predictive analytics using a sample application.
In the "Spark in Action" book, authors Petar Zecevic and Marko Bonaci discuss the Apache Spark framework for data processing (batch and streaming data use cases). They introduce the architecture of Spark and core concepts such as Resilient Distributed Datasets (RDDs). InfoQ spoke with them about Apache Spark, developer tools, and the upcoming features and enhancements in the future releases.
In this article, author discusses the survival prediction of colorectal cancer as a multi-class classification problem and how to solve that problem using the Apache Spark's MLlib Java API.
This article covers machine learning and cognitive computing, and how they are related to artificial intelligence (AI). Panelists discuss how this technology is applied in digital marketing space.