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Bring AI to everyone with an end-to-end, scalable, trusted platform with experimentation and model management

  • Pros

  • Code and designer experience
  • Large range of compute options
  • Good range of built-in Python frameworks
  • Flexible model hosting options
  • Automated machine learning (AutoML)
  • Support for ONNX
  • ML.NET
  • MLOps features
  • Azure Synapse Pipelines integration
  • Cons

  • No serverless SKUs

Read our blog posts about Azure Machine Learning

Exposing legacy batch processing code online using Azure Durable Functions, API Management and Kubernetes

Exposing legacy batch processing code online using Azure Durable Functions, API Management and Kubernetes

Jonathan George

In this post we show how a combination of Kubernetes, Azure Durable Functions and Azure API Management can be used to make legacy batch processing code available as a RESTful API. This is a great example of how serverless technologies can be used to expose legacy software to the public internet in a controlled way, allowing you to reap some of the benefits of a cloud first approach without fully rewriting and migrating existing software.
NDC London Day 1

NDC London Day 1

Ian Griffiths

In this post, Ian describes some of the highlights from the NDC London conference
NDC London Day 3 Retrospective - from personal projects to developer comedy

NDC London Day 3 Retrospective - from personal projects to developer comedy

Jonathan George

Along with several of my endjin colleagues, I attended NDC London in January this year - here's a run through of the sessions I attended on Day 3 and my thoughts. This final day was a mixed bag, taking in talks on drumming and AKKA.net, as well as something a bit more close to home - a session from endjin's own Jess Panni and Carmel Eve on our recent project for OceanMind.