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“Above the Trend Line” – Your Industry Rumor Central for 7/24/2017

Above the Trend Line: your industry rumor central is a recurring feature of insideBIGDATA. In this column, we present a variety of short time-critical news items grouped by category such as people movements, funding news, financial results, industry alignments, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and curious buzz.

“Hide the Tech” to Take Big Data Mainstream

In this contributed article, Ravi Dharnikota, Chief Enterprise Architect at SnapLogic, examines a number of important trends that are simplifying the adoption of big data such as the cloud, serverless computing, self-service integration, and machine learning/AI. The effect is that these trends tend to actually “hide” the tech to put more focus on the data and the business.

Using Python to Drive New Insights and Innovation from Big Data

In a recent white paper “Management’s Guide – Unlocking the Power of Data Science & Machine Learning with Python,” ActiveState – the Open Source Language Company – provides a summary of Python’s attributes in a number of important areas, as well as considerations for implementing Python to drive new insights and innovation from big data.

CASK Data Application Platform Moves Forward

In this video from the DataWorks Summit 2017 conference in San Jose (June 13-15, 2017), insideBIGDATA’s Managing Editor and resident data scientist Daniel D. Gutierrez chats with Nitin Motgi, Founder/CTO at CASK Data.

Book Review: Statistical Learning with Sparsity – The Lasso and Generalizations

As a data scientist, I have a handful of books that serve as important resources for my work in the field – “Statistical Learning with Sparsity – The Lasso and Generalizations” by Trevor Hastie, Robert Tibshirani, and Martin Wainwright is one of them. This book earned a prominent position on my desk for a number of reasons.

Case Study: More Efficient Numerical Simulation in Astrophysics

Novosibirsk State University is one of the major research and educational centers in Russia and one of the largest universities in Siberia. When researchers at the University were looking to develop and optimize a software tool for numerical simulation of magnetohydrodynamics (MHD) problems with hydrogen ionization —part of an astrophysical objects simulation (AstroPhi) project—they needed to optimize the tool’s performance on Intel® Xeon Phi™ processor-based hardware.

“Above the Trend Line” – Your Industry Rumor Central for 7/10/2017

Above the Trend Line: your industry rumor central is a recurring feature of insideBIGDATA. In this column, we present a variety of short time-critical news items grouped by category such as people movements, funding news, financial results, industry alignments, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and curious buzz.

Artificial Musician Builds New Melodies without Music Theory

The “deep artificial composer”, or “DAC” for short, generates brand-new melodies that imitate traditional folk music of Irish or Klezmer origin. It does so without plagiarizing already existing ones, since melodies it writes are as original as those produced by a human composer. The results were presented in April at this year’s edition of the Evostar conference. The DAC actually produces musical scores of melodies, symbolic music written using notation, and does not generate audio files.

Hitachi Solutions Powers Big Data with R

In this video from the EARL 2017 conference in San Francisco (June 5-7, 2017), insideBIGDATA’s Managing Editor and resident data scientist Daniel D. Gutierrez chats with David Bishop, SVP – Head of R&D, Hitachi Solutions America.

TOP 10 insideBIGDATA Articles for June 2017

In this continuing regular feature, we give all our valued readers a monthly heads-up for the top 10 most viewed articles appearing on insideBIGDATA. Over the past several months, we’ve heard from many of our followers that this feature will enable them to catch up with important news and features flowing across our many channels. We’re happy to oblige! We understand that busy big data professionals can’t check the site everyday.