InfoQ Homepage Conferences 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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Refactoring Elixir - Lessons Learned from a Year on Exercism.Io
Devon Estes discusses some common, but less than optimal, solutions to some of the problems on exercism.io followed by refactoring, showing the performance improvements and tradeoffs made.
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Elixir and Money
Tomasz Kowal discusses using Elixir for a financial application, handling rounding errors, designing APIs that gracefully handle network and hardware failures, and crashing the app during design.
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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.