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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

Generally AI: Time to Travel

In this special episode, Roland and Anthony meet at QCon San Francisco to discuss Time and Travel. Roland presents three case studies where temporal misunderstandings in data science led to poor predictive performance. Anthony tells the story of how the first Transcontinental Railroad shortened travel times between the East and West Coasts of the United States.

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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Presentations

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Culture & Methods

Forecasting Using Data

Troy Magennis discusses the top three reasons forecasts fail to match reality, and challenges the assumption that work complexity and effort correlates with delivery time.

Troy Magennis
on Nov 26, 2017

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42:27
AI, ML & Data Engineering

Solving Business Problems Using Predictive Analytics

The panelists discuss solving business problems with predictive analytics.

James Taylor Suchitra Abel P Subrahmanyam Adrian Santos Prateek Joshi Feyzi Bagirov Jack McCallum
on Nov 18, 2017

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01:09:43
AI, ML & Data Engineering

Developing a Machine Learning Based Predictive Analytics Engine for Big Data Analytics

Ali Jalali presents how to develop a machine learning predictive analytics engine for big data analytics.

Ali Jalali
on Oct 16, 2016

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38:53
AI, ML & Data Engineering

Building a Predictive Intelligence Engine

Viral Bajaria explains a formula for reaching the B2B buyer early in the sales cycle by tying together billions of rows of customer data and overlaying predictive intelligence technology.

Viral Bajaria
on Jun 24, 2016

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40:09
AI, ML & Data Engineering

Big-Data Analytics Misconceptions

Irad Ben-Gal discusses Big Data analytics misconceptions, presenting a technology predicting consumer behavior patterns that can be translated into wins, revenue gains, and localized assortments.

Irad Ben-Gal
on May 03, 2016

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35:44

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