Articles

The Problem with AI

AI depends on "data janitorial" work, as opposed to science work, and there is a gulf between prototype and sandbox, and innovation and production.

Virtual Panel: Data Science, ML, DL, AI and the Enterprise Developer

InfoQ caught up with experts in the field to demystify the different topics surrounding AI, and how enterprise developers can leverage them today and thereby render their solutions more intelligently.

Article Series: An Introduction to Machine Learning for Software Developers

Get an introduction to some powerful but generally applicable techniques in machine learning for software developers. 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.

Anomaly Detection for Time Series Data with Deep Learning

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.

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

Yahoo uses Hadoop for different use cases in big data & machine learning areas. They also use deep learning techniques in their products like Flickr. InfoQ spoke with Peter Cnudde on how Yahoo leverages big data platform technologies.

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