Azure Machine Learning is an enterprise-grade AI service that empowers data scientists and developers to efficiently build, deploy, and manage high-quality machine learning models. It accelerates the time to value with a strong focus on industry-leading machine learning operations (MLOps), open-source compatibility, and integrated tools. This trusted AI learning platform is designed to support responsible AI applications in machine learning.

Key Features:

• Accelerate Time to Value: Azure Machine Learning enables the construction of machine learning models by leveraging potent AI infrastructure while orchestrating AI workflows through Prompt Flow, thereby speeding up the process.
• Collaboration and MLOps: The platform supports quick machine learning model deployment, management, and sharing for seamless collaboration across workspaces. It streamlines the MLOps processes.
• Development with Confidence: Azure Machine Learning incorporates built-in governance, security, and compliance measures to ensure safe and reliable machine learning operations.
• Responsible AI: This tool promotes responsible AI practices, facilitating the development of explainable models using data-driven decisions for transparency and accountability.

Support for the End-to-End Machine Learning Lifecycle:

• Prepare Data: This stage includes data labeling, data preparation, and dataset management for data exploration and analysis.
• Build and Train AI and ML Models: Azure Machine Learning supports building and training models, providing compatibility with open-source frameworks like PyTorch and TensorFlow. It enables deep learning and includes features like automation for tabular, text, and image data.
• Validate and Deploy: The platform facilitates model validation and deployment and offers MLOps capabilities for native model management. It also ensures security, responsible AI, and monitoring for deployed models.

Azure Machine Learning for Generative AI:

The tool simplifies the design, evaluation, and deployment of large language model-based applications with prompt flow. It streamlines the entire large language model lifecycle and model management with native MLOps capabilities. The platform supports the use of flexible tools and frameworks, and it offers world-class performance for large-scale AI operations.

Benefits:

• Accelerate time to value with rapid model development.
• Collaborate and streamline model management with MLOps.
• Build enterprise-grade solutions on a hybrid platform.
• Use responsible AI practices throughout the machine learning lifecycle.

Build Your Machine Learning Skills with Azure:

Azure provides resources and hands-on tutorials for learning about machine learning. By participating in a 30-day learning journey, users can enhance their machine learning skills and prepare for the Azure Data Scientist Associate Certification.

Customer Success Stories:

• Airbus: Airbus consolidated 150 data sources to optimize aircraft production using Azure Machine Learning.
• Intuit: Intuit increased company-wide usage of data-driven insights by 10 times with the help of Azure Machine Learning.