InfoQ Homepage Machine Learning Content on InfoQ
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Data Science for Lazy People, Automated Machine Learning
Diego Hueltes discusses using Automated Machine Learning as a personal assistant in Data Science.
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Building Artificial General Intelligence
Peter Morgan takes a look at how deep learning is presently being extended in ways that take AI technologies far beyond the simple image classifiers that they were originally developed to solve.
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Jupyter Notebooks: Interactive Visualization Approaches
Chakri Cherukuri talks about how to understand and visualize machine learning models using interactive widgets and introduces the widget libraries.
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Fairness, Transparency, and Privacy in AI @LinkedIn
Krishnaram Kenthapadi focuses on the application of privacy-preserving data mining and fairness-aware ML techniques in practice, by presenting case studies spanning different LinkedIn applications.
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Michelangelo - Machine Learning @Uber
Jeremy Hermann talks about Michelangelo - the Machine Learning Platform that powers most of the machine learning solutions at Uber.
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Creating Robust Interpretable NLP Systems with Attention
Alexander Wolf introduces Attention, an interpretable type of neural network layer that is loosely based on attention in human, explaining why and how it has been utilized to revolutionize NLP.
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Monitoring AI with AI
Iskandar Sitdikov discusses a solution, tooling and architecture that allows an ML engineer to be involved in delivery phase and take ownership over deployment and monitoring of ML pipelines.
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Migrating ML from Research to Production
Conrado Silva Miranda shares his experience leveraging research to production settings, presenting the major issues faced by developers and how to establish stable production for research.
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Architectures for Big Scale 2D Imagery
Zbigniew Wojna discusses the development of neural architectures for 2D imagery problems in big scale, including analysis of different upsampling methods and mechanism for text recognition and review.
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Building a Voice Assistant for Enterprise
Manju Vijayakumar talks about Einstein Assistant - an AI Voice assistant for enterprises that enables users to "Talk to Salesforce".
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Reasoning about Uncertainty at Scale
Max Livingston presents a case study of using Bayesian modelling and inference to directly model behavior of aircraft arrivals and departures, focusing on the uncertainty in those predictions.
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Machines Can Learn - a Practical Take on Machine Intelligence Using Spring Cloud Data Flow and TensorFlow
Christian Tzolov showcases how building a complex use-case, such as real-time image recognition or object detection, can be simplified with the help of the Spring Ecosystem and TensorFlow.
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