What's cooking in the AWS kitchen? Recipes for a better web (sponsored by Amazon)

Building and maintaining streamlined continuous integration and delivery (CI/CD) pipelines is often challenging. It is even harder on Kubernetes since the deployments are, rightfully so, safely guarde …

Not a day goes by without reading headlines about the fear of AI or how technology seems to be dividing us more than bringing us together. DataKind UK is passionate about using machine learning and artificial intelligence for social good. Kate Vang and Christine Henry explain what socially conscious AI looks like and what DataKind is doing to make it a reality.

Interpretable models result in more accurate, safer, and more profitable machine learning products, but interpretability can be hard to ensure. Michael Lee Williams examines the growing business case for interpretability, explores concrete applications including churn, finance, and healthcare, and demonstrates the use of LIME, an open source, model-agnostic tool you can apply to your models today.

Training models with modern deep learning architecture is often computationally intensive and requires an efficient distributed system at scale. Such systems in distributed machine learning community …

Istio is an open platform that allows the operator to turn workloads into "services" by intent-driven configurations without rewriting/redeploying them. Istio configuration provides the operators cent …

Big data and cloud deployments return huge benefits in flexibility and economics but can also result in runaway costs and failed projects. Drawing on his production experience, Christopher Royles shares tips and best practices for determining initial sizing, strategic planning, and longer-term operation, helping you deliver an efficient platform, reduce costs, and implement a successful project.