InfoQ Homepage Data Content on InfoQ
-
AI, ML and Data Engineering InfoQ Trends Report - August 2021
How AI, ML and Data Engineering are evolving in 2021 as seen by the InfoQ editorial team. Topics discussed include deep learning, edge deployment of machine learning algorithms, commercial robot platforms, GPU and CUDA programming, natural language processing and GPT-3, MLOps, and AutoML.
-
John DesJardins on Continuous Intelligence and In-Memory Computing
In this podcast, John DesJardin, Chief Technology Officer at Hazelcast, met with InfoQ podcast co-host Thomas Betts to discuss the idea of continuous intelligence.
-
Zhamak Dehghani on Data Mesh, Domain-Oriented Data, and Building Data Platforms
In this podcast, Daniel Bryant discussed with Zhamak Dehghani about the motivations for becoming a data-driven organization; the challenges of adapting legacy data platforms and ETL jobs; and how to design and build the next generation of data platforms using ideas from domain-driven design and product thinking, and modern platform principles such as self-service workflows.
-
Fast Data with Dean Wampler
In this podcast, Deam Wampler discusses fast data, streaming, microservices, and the paradox of choice when it comes to the options available today building data pipelines.
-
Martin Hadley on R and the Modern R Ecosystem
In this podcast Werner Schuster talks to Martin Hadley, data scientist at University of Oxford. They discuss the state of the R language, the rich R ecosystem that covers development (RStudio), notebooks for publication (R Notebooks, RPubs), writing web apps (Shiny), and the pros/cons of the different data frames implementations.