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The competitive edge of data science is preserved primarily by 2 things, the sheer volume of the data and the time it takes to understand the nuances. Data repositories in growing organizations are often siloed and the different silos don’t always speak to one another efficiently. Plus the complexity of the data takes teams of data scientists years to understand. Picking up on subtle nuances related to specific businesses or industries is challenging. These 2 things prevent companies that rely on data science from ultimately losing their competitive edge.Read More
Natural Language Processing is a branch of Artificial Intelligence that teaches computers to use language the way people do. When…Read More
Dr. Michael Housman, Chief Data Scientist and Co-Founder of RapportBoost.AI, discusses what to look for when determining the value of data science sources in creating better enterprise artificial intelligence solutions at the JMP Securities Conference panel on AI at the San Francisco Ritz-Carlton in 2017.Read More
Discovering how to efficiently locate, convert, up-sell and retain top customers are key success metrics for any growing company. The…Read More
Algorithms by themselves aren’t valuable. Their ability to solve a particular business problem is. The two most important questions…Read More
The most exciting advance in data science over the past few years is the rapid emergence of deep learning algorithms…Read More