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Responsible Data Science - technical & societal issues

12/2/2019

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Data science is an emerging discipline that offers both promise and peril. Responsible data science refers to efforts that address both the technical and societal issues in emerging data-driven technologies. Dr. Lise Getoor is a computer scientist, professor and research director of the UC Santa Cruz D3 Data Science Research Center and strategic partner of Omny IQ. She is well known for her theoretical work that integrates logic and probability to reason collectively and holistically about context in structured domains. In this video presentation, 

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Early adoptions for AIOps: Obtain Holistic View and Predictive Analytics

10/26/2019

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Omny IQ's AIOps blog
There’s strong interest in applying AIOps, which stands for Artificial Intelligence for IT Operations, as the forces of digital business transformation weigh in on large corporations. Today, many IT professionals believe that AIOps will lead to several strategic benefits. These include increased efficiency, faster remediation, reduced operational complexity, and importantly, improved user experience.

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AI - Apply Statistical Relational Learning in areas of high uncertainty and scale

8/13/2019

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by Jack Van Hel on Unsplash
Machine learning is powerful, and the results we see from deep-learning papers are typically impressive. But can we be confident enough in them to make business decisions that have real, monetary outcomes? For any type of isolated tasks, such as learning to detect a face in an image, or classify a credit card transaction as fraudulent or not, or classify a frequently rebooting device as defective, we can usually construct the relevant low-level features (e.g., pixels, filters, zip codes, vendors, reboots, URLs) and solve the problem using conventional machine learning techniques.

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