AI + machine learning

Microsoft creates deep, technical content to help developers enhance their proficiency when building solutions using the Azure AI Platform.

As companies increasingly look to transform their businesses with AI, we continue to add improvements to Azure AI to make it easy for developers and data scientists to deploy, manage, and secure AI functions directly into their applications.

Along with the general availability of Azure Data Box Edge that was announced today, we are announcing the preview of Azure Machine Learning hardware accelerated models on Data Box Edge.

With ever-increasing data volume and latency requirements, GPUs have become an indispensable tool for doing machine learning (ML) at scale.

As data scientists, we are used to developing and training machine learning models in our favorite Python notebook or an integrated development environment (IDE), like Visual Studio Code (VSCode).

Today we are excited to open source the preview of the NVIDIA TensorRT execution provider in ONNX Runtime.

Azure Machine Learning service is the first major cloud ML service to support NVIDIA’s RAPIDS, a suite of software libraries for accelerating traditional machine learning pipelines with NVIDIA GPUs.

Azure Databricks provides a fast, easy, and collaborative Apache® Spark™-based analytics platform to accelerate and simplify the process of building big data and AI solutions that drive the business forward, all backed by industry-leading SLAs.

We are happy to announce that Microsoft and Intel are partnering to bring optimized deep learning frameworks to Azure. These optimizations are available in a new offering on the Azure marketplace called the Intel Optimized Data Science VM for Linux (Ubuntu).

Azure Databricks provides a fast, easy, and collaborative Apache Spark™-based analytics platform to accelerate and simplify the process of building big data and AI solutions backed by industry leading SLAs.