InfoQ Culture Methods

FEBRUARY 25, 2021

Machine learning is a powerful new tool, but how does it fit in your agile development? Developing ML with agile has a few challenges that new teams coming up in the space need to be prepared for - from new roles like Data Scientists to concerns in reproducibility and dependency management. By Jay Palat.

Machine Learning 133

Machine Learning Artificial Inteligence Agile Development 133

Netflix Tech

JULY 15, 2021

Data Engineers of Netflix?—?Interview Interview with Kevin Wylie This post is part of our “Data Engineers of Netflix” series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. Kevin, what drew you to data engineering?

Data Engineering 75

Data Engineering Engineering Data Big Data 75

InfoQ Culture Methods

JANUARY 7, 2022

This article presents how to use data science to detect wastes and impediments, and concepts and related information that help teams to figure out the root cause of impediments they struggle to get rid of.

Software Development 109

Software Development Data Software Trends 109

InfoQ Culture Methods

FEBRUARY 16, 2023

And even if testing is done, it’s done mostly by developers itself. Have you ever wondered about systems based on machine learning? In those cases, testing takes a backseat. A tester’s role is not clearly portrayed. Testers usually struggle to understand ML-based systems and explore what contributions they can make.

Artificial Inteligence 100

Artificial Inteligence Machine Learning System Testing 100

InfoQ Culture Methods

FEBRUARY 24, 2023

In this article, Tariq King describes the metaverse concept, discusses its key engineering challenges and quality concerns, and then walks through recent technological advances in AI and software testing that are helping to mitigate these challenges.

Testing 127

Testing Engineering Software Artificial Inteligence 127