This is the second installment in a four-part review of 2016 in machine learning and deep learning. Part One, here, covered general trends. In Part Two, we review the year in open source machine learning and deep learning projects. Parts Three and Four will cover commercial machine learning and deep learning software and services. There are thousands of open source projects
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This is the first installment in a four-part review of 2016 in machine learning and deep learning. In the first post, we look back at ML/DL news organized in five high-level topic areas: Concerns about bias Interpretable models Deep learning accelerates Supercomputing goes mainstream Cloud platforms build ML/DL stacks In Part Two, we cover developments in each of the leading open
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ICYMI: Top machine learning (ML) and deep learning (DL) stories from last week. Note to readers: Due to the slower cadence of news as the holidays approach, the daily roundup will be on hiatus until January. Watch for a roundup of the year in machine learning this week, and a look ahead to 2017. Thank you for reading. News — Microsoft
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Machine learning (ML) and deep learning (DL) content from the past 24 hours. Microsoft Releases R Server 9.0 On the Cortana Intelligence and Machine Learning Blog, Microsoft announces Release 9.0 of Microsoft R Server, a bundle of components built on an enhanced R distribution. Highlights of the new release include: — MicrosoftML, a package of machine learning algorithms — Simplified model
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Machine learning (ML) and deep learning (DL) content from the past 24 hours. Good Reads — McKinsey consultants Christoph Glatzel, Matt Hopkins, Tim Lange, and Uwe Weiss explain how retailers use machine learning to drive fresh food stocking. — In IEEE Spectrum, Deliang Wang explains how his lab at OSU uses deep learning to improve hearing aids. People — Unity
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Machine learning (ML) and deep learning (DL) content from the past 24 hours. On Thursday, December 8, Databricks’ Joseph Bradley and Jules Damji will deliver a webinar on migrating Spark ML workloads to DataFrames. Good Reads — On the Algorithmia blog, Matt Kiser explains why deep learning matters. — In The Wall Street Journal’s CIO Journal, Sara Castellanos reports on
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Machine learning (ML) and deep learning (DL) content from the past 24 hours. On the AtScale blog, some old guy says BI-on-Hadoop is dead. People — The folks at DataCamp recognize the five top R package maintainers: Hadley Wickham (ggplot2, dplyr, tidyr,…) Yihui Xie (knitr, bookdown, rmarkdown, shiny, htmlwidgets,…) Dirk Eddelbuettel (Rcpp, RPostgreSQL,…) Jeroen Ooms (jsonlite, xml2,…) Achim Zeileis (colorspace,
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