Microsoft Launches New Azure Machine Learning Tools

Artificial Intelligence is new technology Microsoft has been pushing recently. Today at Ignite, Microsoft launched several new Azure machine learning tools for developers including Learning Experimentation service, Workbench and Model Management service.

Experimentation service allows developers to rapidly prototype on their desktop, then easily scale up on virtual machines or scale out using Spark clusters. Proactively manage model performance, identify the best model, and promote it using data-driven insights. Collaborate and share solutions using popular Git repositories.

Model management is used to deploy and manage your models everywhere. Use Docker containers to deploy models into production faster in the cloud, on-premises, or at the edge. Promote your best performing models into production and retrain them when their performance degrades.

Workbench is a desktop application and command-line interface for Windows and MacOS. Built-in data preparation learns your data preparation steps as you perform them. Project management, run history, and notebook integration bolsters your productivity. Take advantage of the best open source frameworks, including TensorFlow, Cognitive Toolkit, Spark ML, and scikit-learn.

Earlier, Microsoft announced several ML tools for Visual Studio Code Tools for AI supported for developers including CNTK, TensorFlow, and Caffe2.

Visual Studio Code Tools for AI allows developers to build deep learning models and call services straight from your favorite IDE easier with Azure Machine Learning services built right in. Create a seamless developer experience across desktop, cloud, or at the edge.

Another ML tool is MMLSpark that allows developers quickly create powerful, highly-scalable predictive and analytical models for large image and text datasets by using deep learning and data science tools for Apache Spark.

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