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Using Machine Learning with Health Data: The Challenges and Pitfalls

In this contributed article, Elad Ferber, CTO and Co-founder of Spry Health, points out that when considering health data, the level of required customization for machine learning algorithms is very high for 3 reasons: the inherent complexity of the human body, the accessibility and relevance of data sources, and integration into the existing healthcare system.

Interview: David Blei, Professor, Columbia University

The following is a discussion with David Blei, Professor, Columbia University; ACM-Infosys 2013 Foundation Award, ACM Fellow (2015). The Association of Computing Machinery (ACM) just concluded a celebration of 50 years of the ACM A.M. Turing Award (commonly known as the “Nobel Prize of computing”) with a two-day conference in San Francisco. The conference brought together some of the brightest minds in computing to explore how computing has evolved and where the field is headed.

The Rise of the Citizen Data Scientist: Detente in the Era of Data Wars

In this contributed article, Sri Raghavan, Senior Global Product Marketing Manager for Teradata Aster, highlights how the advent of the era of the Citizen Data Scientist is not to be considered a threat to the Data Scientist in the organization. If anything it helps validate the assertions made by Data Scientists about the power of advanced analytics. Having more people like the Citizen Data Scientists attests to the unbridled power of analytics.

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.

An Escape Plan for Modern Businesses Trapped in the Data Dungeon

In this special guest feature, Matt Glickman, VP of Product Management at Snowflake Computing, discusses the tell-tale signs that a DBA is caught in a data dungeon — such as data project failures and limiting data loading to off-peak times to avoid query performance degradation — and how businesses can escape.

Big People in Big Data: How Numbers Propelled them to Success (Or Notoriety)

In this contributed article, Digital Media Manager and Content Writer Sean Westbrook takes a trip down memory lane by remembering the significance of a number of luminaries who have helped shape our big data industry.

Big Data is Transforming the Travel Industry

In this contributed article, tech writer Rick Delgado, examines how the travel industry includes a wide range of businesses, such as rental car companies, hotels, airlines, tour operators, cruise lines and more. Each of these companies must find a way to improve the overall customer experience and to meet the unique needs of each customer, and big data assists with this process.

Big Data Breakthrough: Process Mining

In this special guest feature, Alexander Rinke, co-CEO and co-founder at Celonis, explains how big data – and more specifically process mining – can help organizations gain full transparency into their operations, in turn allowing them to improve margins, business agility and customer service while reducing operational costs.

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.

Implementing AI: When and How?

In this special guest feature, Venkat Viswanathan, Founder and Chairman of LatentView, discusses how organizations determine when artificial intelligence (AI) should be utilized to amplify human intelligence.