ML.Net aims to provide machine learning for .Net developers
Microsoft's new machine learning framework promises high-level APIs to make model training and predictions easy, along with strong integration of .Net language features
Stories by Serdar Yegulalp
What is WebAssembly? The next-generation web platform explained
Learn how WebAssembly is bringing near-native performance to the browser, by allowing devs to build high-speed web apps in the language of their choice
What is a graph database? A better way to store connected data
Learn why graph databases excel at exploring highly connected data, and how to leverage them in your organization
ONNX makes machine learning models portable, shareable
Microsoft and Facebook's machine learning model format aims to let devs choose frameworks freely and share trained models without hassle
Microsoft linker tool shrinks .Net applications
The .Net IL Linker reduces the footprint of .Net apps by discarding unused libraries and references, although it's still in the preview stages
3 projects lighting a fire under machine learning
PyTorch, MXNet, and upstart Java-centric Smile bring greater speed and ease to model training and deployment
Microsoft’s Project Brainwave accelerates deep learning in Azure
Using FPGAs deployed throughout the Azure cloud, Microsoft’s new system for accelerating deep learning poses a challenge to Google’s TPUs
Amazon joins Kubernetes-focused CNCF industry group
Amazon has joined the consortium that supports Kubernetes and the world of containers in the cloud, though its Kubernetes intentions are unclear
IBM speeds deep learning by using multiple servers
IBM's Distributed Deep Learning spreads model training across any number of hardware nodes—as long as they’re IBM nodes
Azure Container Instances: No Kubernetes required
Microsoft's new container service offers a middle ground between Azure Functions and Azure Container Service, with orchestration optional but available
Red Hat's Boltron snaps together a modular Linux server
The Fedora Modular Server project experiments with a new way to deliver multiple versions of packages side-by-side, each with their own development lifecycles
How to get started with Kubernetes
From Hello Minikube to Kubernetes Anywhere to example microservices apps, the options for learning Google’s container orchestration tool abound
Google open-sources TensorFlow training tools
Tensor2Tensor simplifies deep-learning model training so developers can more easily create machine learning workflows
Core ML brings machine learning to Apple developers
Apple's Core ML frameworks provide a standardized -- if limited -- way to embed machine learning into Mac and iOS apps
AMD's game plan to become a machine-learning giant
With machine learning now a major market for GPUs, AMD wants a piece of that action — and an end to Nvidia’s essential monopoly