Artificial Intelligence (AI) & Machine Learning (ML)
Turn meaningful innovation into actionable business results in a reliable and trusted way.
AI is the capability of a machine to imitate intelligent human behavior. Through AI, machines can analyze images, comprehend speech, interact in natural ways and make predictions using data.
Only Microsoft Azure based AI services can empower your organization with:
- Decades of breakthrough research
- AI technology that Microsoft runs on
- The most comprehensive compliance and security offerings
Just some of the exciting Microsoft AI Services available!
Machine Learning – Only Azure empowers you with the most advanced machine learning capabilities. Quickly and easily build, train, and deploy your machine learning models using Azure Machine Learning, Azure Databricks and ONNX.
Use tools and frameworks of your choice without lock-in. Develop models faster using automated machine learning. Easily deploy and manage across the cloud and the edge. A Python-based machine learning service with automated machine learning and edge deployment capabilities.
Azure Data Bricks – An Apache Spark-based big-data service with Azure Machine Learning integration.
ONNX – An open source model format and runtime for machine learning which enables you to easily move between the frameworks and hardware platforms of your choice.
Knowledge Mining – Uncover latent insights from all your content— documents, images, and media – with Azure Cognitive Search. Using the only cloud search service with built-in AI capabilities, discover patterns and relationships in your content, understand sentiment, extract key phrases and more.
Azure Cognitive Search – Only search service with industry leading AI capabilities to easily extract insights from all your content.
Form Recognizer – AI-powered extraction service that transforms your documents and forms into usable data at a fraction of the time and cost.
AI Apps and Agents – Deliver breakthrough experiences in your apps with Cognitive Services and Bot Service. Access industry leading AI models that are being used today by millions in products such as Office 365, Xbox and Bing. Customize these models with your own data and deploy anywhere. Only Azure provides you with access to these battle-tested capabilities.
Cognitive Services – A collection of domain specific pre-trained AI models that can be customized with your data.
BOT Service – A purpose-built bot development environment with out-of-the-box templates to get started quickly.
Microsoft IOT Services – The Azure Internet of Things (IoT) is a collection of Microsoft-managed cloud services that connect, monitor, and control billions of IoT assets. In simpler terms, an IoT solution is made up of one or more IoT devices and one or more back-end services running in the cloud that communicate with each other.
Artificial Intelligence, Machine Learning and IOT Use Cases
Here are real customer business use cases for the Microsoft AI service stack leveraging Azure Machine Learning, Bot Framework, and Cognitive Services can be applied to resolve a variety of challenges in different contexts.
• Online payment fraud detection
• Cache Hit Ratio to improved Web page load time
• Emergency response dashboard
Artificial Intelligence / Big Data Real Time Analytics Solution Architecture
To perform real-time analytical solutions, the ingestion phase of the architecture is changed for processing big data solutions. In this architecture, note the introduction of Apache Kafka for Azure HDInsight to ingest streaming data from an Internet of Things (IoT) device, although this could be replaced with Azure IoT Hub and Azure Stream Analytics. The key point is that the data is persisted in Data Lake Storage Gen2 to service other parts of the solution.
Both the real-time data and batch data is processed in a machine learning model to predict a maintenance schedule for each of the HGVs. This data is made available to the downstream application that third-party garage companies can use if an HGV breaks down anywhere in Europe. In addition, historical reports about the HGV should be visually presented to users. As a result, the following architecture is proposed:
In this architecture, there are two ingestion streams. Azure Data Factory ingests the summary files that are generated when the HGV engine is turned off. Apache Kafka provides the real-time ingestion engine for the telemetry data. Both data streams are stored in Azure Data Lake Store for use in the future, but they are also passed on to other technologies to meet business needs. Both streaming and batch data are provided to the predictive model in Azure Databricks, and the results are published to Azure Cosmos DB to be used by the third-party garages. PolyBase transfers data from the Data Lake Store into SQL Data Warehouse where Azure Analysis Services creates the HGV reports by using Power BI.
Click here to read a Microsoft White Paper.
Click here for some real-life Microsoft Customer Stories
Contact the data experts at Oakwood today for further information and service offerings.