InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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Monitoring Modern Architectures with Data Science
Dave Casper talks about how modern data science and algorithms are being applied to "fight machines with machines".
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Bias in BigData/AI and ML
Leslie Miley discusses how inherent bias in data sets has affected things from the 2016 Presidential race to criminal sentencing in the United States.
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Handling Billions of Edges in a Graph Database
Michael Hackstein discusses graph databases, the current scalability problems and their solutions.
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Cognitive Services, Next Step in Creating Our Robot Overlords
Harold Pulcher discusses Cognitive Services, how to get started using them, and how to incorporate speech, image, and facial recognition into an application.
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Production Machine Learning
Jan Machacek discusses the challenges in writing deep learning code, testing and validating data management, environments, model storage & serving, validating data reporting, and CI&CD.
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The Practice & Frontiers of AI Panel
The panelists discuss where AI is heading and how it's affecting software today.
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Panel: SQL over Streams, Ask the Experts
The panelists discuss the new generation of Stream Processing engines.
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The Joy of Stochastic Gradient Descent
Carin Meier takes a look at the joys of Deep Learning, discussing how Deep Learning is changing how people approach programming, communicate with each other, and even what it means to be human.
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Solving Business Problems Using Predictive Analytics
The panelists discuss solving business problems with predictive analytics.
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A Cloud-centric Ecosystem Approach to Ease IoT Development
Yujing Wu discusses two use cases of a cloud-based IoT ecosystem that enables IoT device communication across silos and interoperability across different vendors.
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AI in Finance: from Hype to Marketing and Cybersec Applications
Natalino Busa illustrates a number of use cases of using AI and machine learning techniques in finance, such as transaction fraud prevention and credit authorization.
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Julia: A Modern Language for Modern ML
Simon Byrne and Viral Shah talk about Julia, a modern high-performance, dynamic language for technical computing, with many features which make it ideal for machine learning.
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