Blogs

Q&A on the Book Agile Machine Learning

Infoq

The book Agile Machine Learning by Eric Carter and Matthew Hurst describes how the guiding principles of the Agile Manifesto have been used by machine learning teams in data projects.

Visit Site

Q&A on the Book Agile Machine Learning
Natural Language Processing with Java - Second Edition: Book Review and InterviewInfoq Why the Dual Operating Model Impedes Enterprise AgilityInfoq How to Spark a Consumer-Grade UX RevolutionInfoq Software Testing, Artificial Intelligence and Machine Learning Trends in 2023Infoq Grab Redesigns Counter Service Storage for 50% Lower P99 LatencyInfoq The Async Multiprocessing Has Sound Foundations in Linux, But Further Testing is NeededInfoq How a marketing agency increased client conversions 35% with Zapier CanvasZapier Lessons Swift Designer Chris Lattner Has Learned about LeadershipThenewstack Summer Data Engineering RoadmapMotherduck Capturing Logs in Docker DesktopDocker How To Create and Use Avatars in eLearningHeygen From Hawking to Siri: The Evolution of Speech SynthesisDeepgram How Sky Italia Digitizes Learning Paths to Accelerate New Product Launches by 4xSynthesia How EPOS achieved a 90% learning completition rate with AI video.Synthesia How Mondelez Accelerates Supply Chain Training Across 150+ Global Manufacturing PlantsSynthesia Training: Hard Work Pays off for Data/AI ProsThenewstack Breakdown: The Kubernetes-Run AI Video Generation Pipeline for NIUS.TVThenewstack Cerebras Architecture Deep Dive: First Look Inside the HW/SW Co-Design for Deep Learning [Updated]Cerebras Cirrascale Cloud Services® and Cerebras Systems Announce Availability of Cerebras Cloud @ CirrascaleCerebras DockerCon Workshops: Getting Started with Docker, AI/ML, Secure DevelopmentDocker