MLOps on Azure Databricks with MLflow
Explore MLOps on Azure Databricks with MLflow, focusing on Model Registry, Webhooks, and automated pipelines for effective machine learning model lifecycle management and deployment.
Understanding the Machine Learning Process and Embedding Models into Apps
Learn to build ML models with Azure ML and VS Code, operationalize them in apps, and implement MLOps practices. Covers PyTorch Lightning, model prediction, and integration with DevOps and Kubernetes.
VS Code, Azure ML, and GitHub Codespaces
Configure VS Code for Azure ML projects on GitHub Codespaces, a cloud-based development environment. Learn setup, extension management, and terminal customization for efficient cloud-based machine learning workflows.
Accelerating AI and ML Insights with Azure ML and Teradata VantageCloud
Discover how Teradata VantageCloud and Azure ML integration accelerates AI and ML insights at scale, overcoming deployment challenges and unlocking data-driven value for organizations.
Building Powerful AI Apps with Copilot in Microsoft Fabric - BRK225
Explore Copilot in Microsoft Fabric to build AI apps, increase developer productivity, and empower data professionals. Learn to train custom ML models and bridge business intelligence with AI using Semantic Link.
Building Real-Time Sentiment Pipeline for Live Tweets
Learn to build a real-time predictive analytics pipeline for Twitter sentiment analysis using Azure ML, R, and Python. Covers model creation, cloud deployment, and live dashboarding with PowerBI.
Building and Deploying a Model Using AutoML in Azure ML - Azure Tutorial for Beginners
Learn to streamline machine learning model development with Azure AutoML. Explore algorithm selection, hyperparameter tuning, and evaluation metrics for efficient model creation and deployment.
Productionizing Machine Learning Pipelines with Databricks and Azure ML
Jumpstart ML projects with Databricks and Azure ML. Learn to build, track, and deploy production-ready pipelines using tools like MLflow, TensorFlow, and PyTorch for efficient, reproducible data science workflows.
Build Systems of Intelligence with Power BI and Azure Data
Learn how Power BI integrates with Azure services to build and manage enterprise-scale business intelligence, covering data prep, distribution, governance, performance, and security.
Rise of the Machines
Explore machine learning and predictive analytics with Azure ML in this primer, led by Microsoft's Director of Architecture Josh Holmes.
Hidden Differences Between Azure ML Products Revealed
Explore Azure ML products, their differences, and use cases. Learn to create end-to-end ML workflows, integrate with SQL Server, and manage models in production using various Azure tools.
MLflow - Platform for Complete Machine Learning Lifecycle
Discover how MLflow simplifies machine learning development by tracking experiments, registering projects, and streamlining model deployment across various platforms.