How to democratize machine learning across the enterprise
By Dave Kang, contributing writer for Informationweek.com
Prior to machine learning (ML), complex and large-scale data set analysis was conducted by statisticians. Today, organizations rely increasingly on ML to do this work with greater accuracy, speed, and scale. As more companies move to the cloud and begin managing big data, business leaders are now asking how they can scale data science and ML capabilities to improve the bottom line.
Decision Intelligence: Turning hotel analytics into action
By Axis Rooms, contributing writers for Hospitalitynet.org
From the immense amount of data that organizations receive, very few have the ability or the know-how to utilize it to their benefit. When an organization tracks data to identify opportunities, minimize risks and optimize the way business is conducted, it is referred to as business intelligence.
How artificial intelligence can improve organizational decision making
By Milan Dordevic, contributing writer for Forbes.com
Artificial intelligence (AI) is reimagining the business world, boosting innovation and productivity, and helping organizations think bigger. Organizations can use AI to improve their products, processes, and decision-making. Using the technology available today, organizations should be able to achieve organizational agility powered by AI.
Find the right pace for your AI rollout
By Rebecca Karp, contributing writer for HBR.org
Machine learning, deep learning, and other artificial intelligence technologies promise to significantly reshape the workplace. They can reduce redundant tasks, automate work, and improve organizational capabilities. Yet for most companies, the potential of these technologies is still out of reach. As a recent census study shows, less than 7% of organizations have adopted AI technologies. Why?
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