Tag Archives: Databricks

The Year in Machine Learning (Part Four)

This is the fourth installment in a four-part review of 2016 in machine learning and deep learning. — Part One covered Top Trends in the field, including concerns about bias, interpretability, deep learning’s explosive growth, the democratization of supercomputing, and the emergence of cloud machine learning platforms. — Part Two surveyed significant developments in Open Source machine learning projects, such as R, Python, Spark, Flink,

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The Year in Machine Learning (Part Two)

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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Roundup 10/31/2016

Top machine learning (ML) and deep learning (DL) stories from last week. Plus some good reads, and special Halloween content. The featured image comes from MIT’s Nightmare Machine. Horrifying AI/ML/DL — Aussie bots that hunt down and kill small animals. — Bots with knives that cut flesh. — Machines that hunt and kill humans. — IBM Watson engines that profile you and sell

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Roundup 10/28/2016

Machine learning (ML) and deep learning (DL) content from the past 24 hours. Plus, some AI stuff. I’m publishing a three-part series on the state of enterprise machine learning in The Next Platform. Part one is here. Good Reads — Helen Beers explains AI in the second part of a series. Part one is here. — Market Realist publishes a twelve-part

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Databricks Releases Spark Survey

In a press release and blog post, Databricks announces results from its 2016 Spark Survey. Databricks surveyed 1,615 Spark users and prospective users in July, 2016 Respondents include data engineers, data scientists, architects, technical managers, and academics. Key findings from the survey: Spark SQL remains the most widely used component. 88% use Spark SQL 71% use Spark Streaming 71% use

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Big Analytics Roundup (September 12, 2016)

On a Google blog, Kaz Sato describes how a Japanese farmer uses TensorFlow to classify cucumbers. Very good. Perhaps now Google can set TensorFlow to work figuring out how to comply with EU regulations. Good Reads Adrian Colyer returns for the Fall semester with daily papers. Superlative Reads Dez Blanchfield heaps praise on obscure blogger’s new book. HPE Holds a Fire Sale

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