In this article, we'll talk 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 brief descriptions of feed-forward neural networks and recurrent neural networks, and describes how to build a recurrent neural network that detects anomalies in time series data. To make our discussion concrete, we’ll show how to build a neural network using Deeplearning4j, a popular open-source deep-learning library for the JVM.
This article addresses a few examples of issues when using machine learning to solve real-world problems and hopefully provides some suggestions (and inspiration) for how to overcome the challenges.
In this article, we present an extended “case study” in Python: how can we build a machine learning model to detect credit card fraud?
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.
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 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
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.