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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.

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.

Software Finds a Way: Why CPUs Aren’t Going Anywhere in the Deep Learning War

In this contributed article, Adi Pinhas, CEO of Brodmann17, examines how Application Specific Integrated Circuits, or ASICs, are predicted to be the new technology built for deep learning. Unlike GPUs, which were built for graphic processing ASICs designed specifically for deep learning have better price/performance and power/performance ratios.

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.

Peering into Neural Networks

Neural networks, which learn to perform computational tasks by analyzing large sets of training data, are responsible for today’s best-performing artificial intelligence systems, from speech recognition systems, to automatic translators, to self-driving cars. But neural nets are black boxes. Once they’ve been trained, even their designers rarely have any idea what they’re doing — what data elements they’re processing and how.

How R Powers Data Science at Microsoft

In this video “How R Powers Data Science at Microsoft” 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 Vijay K. Narayanan – Director, Algorithms and Data Science Solutions, Microsoft.

Big Data Project Failure Pain Points and their Solution

Big data projects don’t typically fail for a single reason, and certainly not for technology alone. A combination of factors serve to derail big data deployments. Problems and failures occur due to factors including business strategy, people, culture, inattention to analytics details or the nuances of implemented tools, all intensified by the rapid advancement of digital transformation.

Creating a Data-Based and Client-Focused Culture

In the world of social media, increasingly quick-moving communication amid rapidly growing data, a company’s culture defines its reputation, and its reputation often defines its success – or failure. Clarity Insights shares how companies can create a data-based and client-focused culture from the top down.