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Development

Featured in Development

Unleashing the Kernel With eBPF

Liz Rice uses demos and examples to explain how eBPF works, and why the ability to customize the kernel’s behavior leads to powerful and efficient capabilities.

All in development

Architecture & Design

Featured in Architecture & Design

Empirical Observations on the The Future of Scalable UI Architecture

Willian Martins discusses a concise course of action regarding the patterns to introduce into a UI system and how to build UI architectures for scale.

All in architecture-design

AI Infrastructure

Featured in AI, ML & Data Engineering

Denys Linkov on Micro Metrics for LLM System Evaluation

Live from the QCon San Francisco Conference, we are talking with Denys Linkov, Head of Machine Learning at Voiceflow. Linkov shares insights on using micro metrics to refine large language models (LLMs), highlighting the importance of granular evaluation, continuous iteration, and rigorous prompt engineering to create reliable and user-focused AI systems.

All in ai-ml-data-eng

Culture & Methods

Featured in Culture & Methods

Building Effective Engineering Teams and Avoiding Cargo Cult Practices

In this podcast Shane Hastie, Lead Editor for Culture & Methods spoke to David Guttman about building effective engineering teams, avoiding common pitfalls, critiques of cargo cult practices, building great engineering culture and the importance of individual accountability.

All in culture-methods

DevOps

Featured in DevOps

From Anti-patterns to Best Practices: A Practical Guide to DevSecOps Automation and Security

Spyros Gasteratos discusses security patternsand provides alternatives to detrimental practices, along with a compilation of free and open-source tools endorsed by the community.

All in devops

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InfoQ Homepage Presentations Google Dataflow Codelab

AI, ML & Data Engineering

Google Dataflow Codelab

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48:17

Summary

Martin Gorner introduces Google Dataflow Codelab, and demos the tools and techniques they are using for data science.

Bio

Martin Gorner is passionate about science, technology, coding, algorithms and everything in between. He joined Google Developer Relations in 2011 and now focuses on parallel processing and machine learning (Dataflow and Tensorflow).