Roundup 11/30/2016

Machine learning (ML) and deep learning (DL) content from the past 24 hours.


— Spark Summit East meets in Boston February 7-9 2017.

Good Reads

— From Moor Insights & Strategy, an excellent paper on trends in predictive maintenance, a key application for machine learning. (Update: A reader notes that this is a sponsored paper, which is true, but I have no business relationships with the author or sponsor and thought it was a good read anyway.)

— In The Next Platform, Nicole Hemsoth explains the supercomputing vision of NVIDIA CEO Jen-Hsun Huang.

Scenes of the Future

An MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) deep learning system produces videos that predict what will happen next in a scene based on a single image from that scene. In ZDNet, Liam Tung reports. Linkapalooza here.


— Max Kuhn, author of Applied Predictive Modeling and progenitor of the caret package for machine learning moves to RStudio.

Methods and Techniques

— On, Matthew Corrigan introduces you to machine learning with Python and perceptrons.


— At AWS’ re:Invent Conference, Databricks announces HIPAA compliance for its Apache Spark managed service. Databricks has also achieved AWS Public Partner status.

— In ZDNet, George Anadiotis touts the latest release of Birst, a BI tool with some embedded ML capabilities. He mentions automated machine learning, but it’s clear that he has no idea what he’s talking about. Pro tip: if you think that BeyondCore is an example of automated machine learning, go to the back of the class.

— Splice Machine ships Release 2.5 of its eponymous product. The press release mentions machine learning but the product has no ML capability, so I guess it’s all about SEO.

— TensorFlow v0.12.0 RC0 is now available, and it runs on Microsoft Windows. Features available on Windows are a subset of the full feature set. For details, read the announcement.

— In Fortune, Barb Darrow explains why AWS has standardized on MXNet for deep learning.

— Fujitsu introduces consulting services to help customers accelerate their use of machine learning and AI.


— In Next Big Future, Brian Wang swoons over the NVIDIA Xavier chip and its potential for deep learning.


— A startup named ebo uses a neural network to help you choose gifts for people. The service is still in preview. Michael Irving reports.

— GE Healthcare and Boston Children’s Hospital partner to develop deep learning tools for pediatric brain scans.

— In MIT Technology Review, Will Knight describes how a Google eye scanning algorithm can diagnose diabetic retinopathy better than human experts can. On the Google blog, Lily Peng explains. The JAMA paper is here.

— In Security Week, Kevin Townsend explains how machine learning helps criminals attack systems. Hey, machine learning doesn’t do bad things, people do bad things.

— On the Yelp Engineering blog, Alex M. describes how he used deep learning to find beautiful photos on Yelp.


— Sanghamitra Kar profiles Delhi-based Lybrate, a startup that uses ML for healthtech.

— Petuum Inc, a spinout from Carnegie Mellon University, lands $15 million in venture capital to “democratize” machine learning.

— The Cortana Intelligence and Machine Learning Blog explains how Microsoft shares machine learning and data science within the enterprise.

Bottom Story of the Day

— In The Eponymous Pickle, Franz Dill reports on sex as an algorithm.


  • “From Moor Insights & Strategy, an excellent paper on trends in predictive maintenance…” >> excepts that it really feels like a sponsored paper featuring HPE Edgeline Converged IoT Systems, HPE Edgeline Intelligent Gateways, HPE Aruba networking equipment & software … and indeed the final disclosure states that “This paper was commissioned by Hewlett Packard Enterprise.”

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