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Top 10 2017 Big Data White Papers: Data Science, Machine Learning, AI, Deep Learning & More

In this continuing regular feature, we give all our valued readers an annual heads-up for the top 10 most downloaded articles appearing on insideBIGDATA. Over the past several months, we’ve heard from many members of our audience 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.

Where Are We with Computer Vision?

In this article, I’d like to share a nice summary of the state of computer vision from Course 4 “Convolutional Neural Networks” from the new Deep Learning Specialization series on Coursera. Dr. Andrew Ng provides some compelling observations about deep learning and computer vision with the goal of mapping out the future of this increasingly popular technology.

Dedicated Precision Medicine Solution is Key to Value-Based Success

In this special guest feature, Terry Macaleer, President at Orion Health U.S., discusses how precision medicine is an emerging approach to identifying precisely those treatments that will work for a given patient, based upon terabytes of the patient’s—and countless other patients’—genomic and other “-omic” data. He also highlights how the winning precision medicine solution will be provided by an agnostic health IT vendor, not an EMR vendor who isn’t open to third-party solutions working in conjunction with their EMR offerings.

TOP 10 insideBIGDATA Articles for December 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.

The Future of Artificial Intelligence – What Will it Look Like?

In this contributed article, Anabel Cooper, a 26-year old editor and writer from Harlow with a deep interest in technology, takes a look at the future of artificial intelligence and what it will look like.

Using Artificial Intelligence to Analyze All Fashion Customer Data

“Can a global brand really live up to the needs of diverse cultures from Latin America to Eastern Europe all the way to Asia without putting its identity on the line?” (McKinsey) The differences in expectations and desires from country to country are massive. It is a big challenge for global retailers to properly segment and market to their increasingly diverse international buyers.”

An Introduction to NoSQL Databases

In the video presentation below, Bart Baesens, Professor of Big Data & Analytics, discusses a series of non-relational database management systems which focus specifically on being highly scalable in a distributed environment: NoSQL databases. The presentation is an extract from an upcoming book Principles of Database Management.

5 Misconceptions About Data Science

In this contributed article, technology writer and blogger Kayla Matthews examines the 5 most common misconceptions floating around about data science and what project administrators and business managers need to be aware of. Remember these tips before getting involved, and be sure to do the necessary research. With the right people and knowledge on your side, you’ll be on your way in no time, rocketing to success.

The Data Scientist’s Guide to Apache Spark

Looking to dive deeper into the more cutting edge machine learning use cases in Apache Spark? To successfully use Spark’s advanced analytics capabilities including large scale machine learning and graph analysis, check out The Data Scientist’s Guide to Apache Spark, from our friends over at Databricks.

The heroic Data Engineer – Lending a Helping Hand to Data Drowned Scientists

In this contributed article, Ida Jessie Sagina, a content marketing specialist at Mobius Knowledge Services, discusses the important role of the data engineer in today’s enterprise, and how to lay those data pipes and save the lives of drowning analysts and data scientists.