InfoQ Homepage QCon New York 2017 Content on InfoQ
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The Marriage of Communication and Code
Scott Ford and Andrea Goulet discuss how communication and code are inextricably linked and share their top five tips with the audience so one can immediately improve communication.
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Getting Old(er) in Tech: Staying Relevant
Don Denoncourt talks about how to stay relevant in the tech industry, ways to keep coding skills sharp, no matter how old we are, perspectives for technical growth and how to be a lifelong learner.
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The Effective Remote Developer
David Copeland talks about what one can do to be at their best as a remote team member, as well as what one needs from environment, team, and company.
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Machine Learning in Academia and Industry
Deborah Hanus discusses some of the challenges that can arise when working with data.
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Real-World Virtual Reality
Alex Kesling explores Google Expeditions as a case study in building meaningful Virtual Reality applications.
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Modern Distributed Optimization
Matt Adereth talks about the Black-box optimization techniques, what’s actually going on inside of these black-boxes and discusses an idea of how they can be used to solve problems today.
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What Came First: The Ordering of Events in Systems
Kavya Joshi explores the beautifully simple happens-before principle and delves into how happens-before is tracked in a distributed database like Riak.
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Automating Inventory at Stitch Fix
Sally Langford talks about the use of ML within StitchFix’s inventory forecasting system, the architecture they have developed in-house and their use of Bayesian methods.
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Solving Payment Fraud and User Security with ML
Soups Ranjan talks about Coinbase’s risk program that relies on machine learning (supervised and unsupervised), rules-based systems as well as highly-skilled human fraud fighters.
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Evaluating Machine Learning Models: A Case Study
Nelson Ray talks about on how to estimate the business impact of launching various machine learning models, in particular, those Opendoor uses for modeling the liquidity of houses.
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Semi-Supervised Deep Learning on Large Scale Climate Models
Prabhat presents NERSc’s results in applying Deep Learning for supervised and semi-supervised learning of extreme weather patterns, scaling Deep Learning to 9000 KNL nodes on a supercomputer.
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API Design Lessons Learned: Enterprise to Startup
Mohamed El-Geish explores lessons learned at big companies like Microsoft and LinkedIn, and adapts the insights drawn from them to fit a fast-growing startup.
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