InfoQ Homepage Presentations
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Orchestrating Data Microservices with Spring Cloud Data Flow
Mark Pollack discusses how to create data integration and real-time data processing pipelines using Spring Cloud Data Flow and deploy them to multiple platforms – Cloud Foundry, Kubernetes, and YARN.
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Rapidly Develop, Deploy and Scale Java Cloud Apps Using Spring Boot
Asir Selvasingh demos building and deploying Java apps and microservices across multiple datacenters.
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SpringOne 2017 Closing Keynote: A Look to the Future
The panelists talk about the future of the platforms and the impact of AI and ML, how to infuse a large organization with a startup mentality, the movement of the open internet and more.
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Culture May Eat Agile for Breakfast
Stefan Wolpers discusses how to deal with new hires and how to integrate them into the culture of an organization.
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Decentralized Governance for the Masses
Kent Dahlgren discusses the designs and approaches chosen in developing a decentralized governance solution for people with low income and modest resources.
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Building a Culture of Continuous Improvement
Kevin Goldsmith shows what Avvo has done to build a foundation for a continuous improvement culture.
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Observable JS Apps
Emily Nakashima talks about an event-driven approach to client-side observability for the most complicated parts of Honeycomb's customer-facing React app: the query builder.
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WebAssembly (And the Death of JavaScript?)
Colin Eberhardt looks at what's wrong with the way people are using JavaScript today and why they need WebAssembly.
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Reinventing npmjs.com
Katie Fenn talks about the process of architecting the new npmjs.com website, and examines how the changing landscape of development tooling has shaped it throughout its lifetime.
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Models in Minutes not Months: AI as Microservices
Sarah Aerni talks about how Salesforce built an AI platform that scales to thousands of customers.
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Understanding ML/DL Models using Interactive Visualization Techniques
Chakri Cherukuri discusses how to use visualization techniques to better understand machine learning and deep learning models.
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Interpretable Machine Learning Products
Mike Lee Williams discusses how interpretability can make deep neural networks models easier to understand, and describes LIME, an OS tool that can be used to explore what ML classifiers are doing.
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