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Beyond Big Data: Why AI Requires Getting Small Data Right

In this special guest feature, Maciej Gryka, Head of Data Science at Rainforest, discusses why big data in the context of AI leads us to ask some serious questions about the future of big data. Data scientists often wonder whether we need big data as much as some think. In many cases the answer is “no” and instead of going big, what we really need to be doing is thinking smaller. Read on to learn why.

Artificial Intelligence is Innovating Your Healthcare Needs in 2018

In this contributed article, freelance human Avery Phillips takes a look at how artificial intelligence (AI) is making significant inroads into healthcare innovation as we move into 2018. One of the biggest benefits is that healthcare providers can use this technology to help promote better lifestyle choices to their patients and others.

Sports, Taxes, Criminal Investigations and Elections: Practical Use Cases for Data Preparation?

In this special guest feature, Jon Pilkington, Chief Product Officer at Datawatch, discusses how self-service data preparation solutions are often work-life hacks, enabling users to easily derive business insights that impact a corporation’s bottom-line. But, the use cases for this technology are actually quite widespread. The article provides 4 unique ways data preparation technology assists in predicting outcomes and significantly improving everyday life.

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.

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.”

Seeing the Light on the Positive Impacts of AI/ML for Retailers

In this special guest feature, Tom Buiocchi, CEO of ServiceChannel, discusses how new technologies such as AI/ML and modern facilities management (FM) software can help retailers be on the “right” side of creative destruction, a process where new technologies disrupt old ways of doing things in favor of more speed, automation, intelligence, and efficiency.

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 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.