InfoQ Homepage QCon Software Development Conference Content on InfoQ
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Deep Learning at Scale
Scott Le Grand describes his work at NVidia, Amazon and Teza, including the DSSTNE distributed deep learning framework.
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Building Robust Machine Learning Systems
Stephen Whitworth talks about his experience at Ravelin, and provides useful practices and tips to help ensure our machine learning systems are robust, well audited, avoid embarrassing predictions.
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Taming Complexity with Object-Oriented UX
Sophia Voychehovski discusses all the factors that cause complexity, the three key ways one can wrangle it and object-oriented UX.
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Further Together: Curated Pairing Culture @Pivotal
Neha Batra presents her experience with pair programming at Pivotal Labs. They pair program eight hours/day every workday and help enable other companies to practice it with them.
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Performance and Search
Dan Luu discusses how to estimate performance using back of the envelope calculations that can be done in minutes or hours, even for applications that take months or years to implement.
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Design Guidelines for Conversational Interfaces
Angie Terrell discusses the current state of conversational interfaces and human-centered design principles to guide the design of conversational apps.
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Scaling up Near Real-Time Analytics @Uber &LinkedIn
Chinmay Soman and Yi Pan discuss how Uber and LinkedIn use Apache Samza, Calcite and Pinot along with the analytics platform AthenaX to transform data to make it available for querying in minutes.
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Real-Time Recommendations Using Spark Streaming
Elliot Chow discusses the data pipeline that they built with Kafka, Spark Streaming, and Cassandra to process Netflix user activities in real time for the Trending Now row.
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Engineering You
Lynn Langit and Martin Thompson explore the individual practices and techniques that can help bring out the engineer in us.
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Effective Data Pipelines: Data Mngmt from Chaos
Katharine Jarmul discusses implementation decisions for those looking for a practical recommendation on the "what" and "how" of data automation workflows.
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The Move to AI: from HFT to Laplace Demon
Eric Horesnyi and Albert Bifet discuss how hedge funds have moved beyond High Frequency Trading using AI and real-time data processing.
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Building Data Pipelines in Python
Marco Bonzanini discusses the process of building data pipelines and all the steps necessary to prepare data, focusing on data plumbing and going from prototype to production.
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