With the exponential rise of data, we are undergoing a technology transformation, as organizations realize the need for insights driven decisions. Artificial intelligence (AI) and machine learning (ML) technologies can help harness this data to drive real business outcomes across industries. Azure AI and Azure Machine Learning service are leading customers to the world of ubiquitous insights and enabling intelligent applications such as product recommendations in retail, load forecasting in energy production, image processing in healthcare to predictive maintenance in manufacturing and many more.
AI は、世界を変える大きなイノベーションの波を起こす原動力となっています。Microsoft の目標は、組織が Azure AI を通じてビジネスのあらゆる面に AI を適用することで、顧客と関わり、従業員を力づけ、運用を最適化し、製品を変革できるように支援することにあります。これを実現するために、Microsoft には、指標となる 3 つの投資原則があります。
Recommendation systems are used in a variety of industries, from retail to news and media. If you’ve ever used a streaming service or ecommerce site that has surfaced recommendations for you based on what you’ve previously watched or purchased, you’ve interacted with a recommendation system.
DevOps is the union of people, processes, and products to enable the continuous delivery of value to end users. DevOps for machine learning is about bringing the lifecycle management of DevOps to Machine Learning.
When it comes to executing a machine learning project in an organization, data scientists, project managers, and business leads need to work together to deploy the best models to meet specific business objectives.
Everyone’s talking about machine learning (ML). Business decision makers are finding ways to deploy machine learning in their organizations. Data scientists are keeping up with all the advancements, tools, and frameworks available.
Microsoft creates deep, technical content to help developers enhance their proficiency when building solutions using the Azure AI Platform.
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.
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).
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).