InfoQ Homepage QCon Software Development Conference Content on InfoQ
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Visual Intro to Machine Learning and Deep Learning
Jay Alammar offers a mental map of Machine Learning prediction models and how to apply them to real-world problems with many examples from existing businesses and products.
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Lessons Learned from Reviewing 150 Infrastructures
Jon Topper presents a structured review of the architectural and operational choices of 150 platform teams, talking about common mistakes and providing advice on how to avoid these.
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Evolution of Financial Exchange Architectures
Martin Thompson looks at the evolution of financial exchanges and explores what is considered state of the art today.
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Does Java Need Inline Types? What Project Valhalla Can Bring to Java
Sergey Kuksenko talks about the performance benefits inline types bring to Java and how to exploit them. Inline/value types are the key part of experimental project Valhalla.
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Monitoring All the Things: Keeping Track of a Mixed Estate
Luke Blaney talks about how to approach monitoring an estate of many technologies and what the Financial Times did to improve visibility across systems built by all its teams.
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Leading a Journey to Better Quality
Maryam Umar talks about the steps she took to define the term 'bad quality' and how to better discover it as an earlier part of the software delivery process rather than as feedback from the customer.
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Introducing and Scaling a GraphQL BFF
Michelle Garrett talks about the journey of introducing and then scaling a GraphQL BFF to serve multiple applications.
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Optimize for Time
Andy Walker gives advice on how to use time in a way that enables teams to improve. He shares practical advice on how to get the most out of the time, and proposes principles to develop approaches
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How We Built a Generative Culture at Redgate
Jeff Foster talks about the Westrum model of culture and shares some practical steps that Redgate has taken to improve the way they build products by building a generative culture.
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Accuracy as a Failure
V. Warmerdam talks about cautionary tales of mistakes that might happen when we let data scientists on a goose chase for accuracy. Highly accurate models are more damaging than the inaccurate ones
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Why Distributed Systems Are Hard
Denise Yu talks about the complexity of distributed systems and why one needs to account for the human factor when designing a complex system.
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