Machine Learning

Machine Learning

Azure Machine Learning is a cloud service for accelerating and managing the machine learning project lifecycle. Machine learning professionals, data scientists, and engineers can use it in their day-to-day workflows: Train and deploy models, and manage MLOps.

You can create a model in Azure Machine Learning or use a model built from an open-source platform, such as Pytorch, TensorFlow, or scikit-learn. MLOps tools help you monitor, retrain, and redeploy models.

Azure Machine Learning

Azure Machine Learning is for individuals and teams implementing MLOps within their organization to bring machine learning models into production in a secure and auditable production environment.

Data scientists and ML engineers will find tools to accelerate and automate their day-to-day workflows. Application developers will find tools for integrating models into applications or services. Platform developers will find a robust set of tools, backed by durable Azure Resource Manager APIs, for building advanced ML tooling.

Enterprises working in the Microsoft Azure cloud will find familiar security and role-based access control (RBAC) for infrastructure. You can set up a project to deny access to protected data and select operations.

Productivity for everyone on the team

Machine learning require a team with varied skill set. Azure Machine Learning

• Collaborate with your team via shared notebooks, compute resources, data, and environments
• Develop models for fairness and explainability, tracking and auditability to fulfill lineage and audit compliance requirements
• Deploy ML models quickly and easily at scale, and manage and govern them efficiently with MLOps
• Run machine learning workloads anywhere with built-in governance, security, and compliance

Tools that meet our needs

Anyone on an ML team can use their preferred tools to get the job done. Whether we're running rapid experiments, hyperparameter-tuning, building pipelines, or managing inferences, we can use familiar interfaces including:

• Azure Machine Learning studio
• Python SDK (v2)
• CLI (v2))
• Azure Resource Manager REST APIs

Enterprise-readiness and security

Azure Machine Learning integrates with the Azure cloud platform to add security to ML projects.

Security integrations include:

• Azure Virtual Networks (VNets) with network security groups
• Azure Key Vault where you can save security secrets, such as access information for storage accounts
• Azure Container Registry set up behind a VNet

Multinode distributed training

Efficiency of training for deep learning and sometimes classical machine learning training jobs can be drastically improved via multinode distributed training. Azure Machine Learning compute clusters offer the latest GPU options.

Supported via Azure ML Kubernetes and Azure ML compute clusters:

• PyTorch
• TensorFlow
• MPI

GTech Learn

GTechLearn is a Microsoft official training provider and consulting company in North America and South Asia.

GTechLearn has a pool of certified and skilled resources that it can offer extensive trainings to clients. We are also the Microsoft authorized Online Services Distributer and Authorize to sell & implement products like MS Office 365, Dynamics 365 for both Online & On Premise with many more cloud based services.

Services Offered

• Self-Paced Courses
• Cloud Migration
• Office 365 Implementation & Support
• Dynamics 365 Implementation & Support
• Microsoft Official Training
• Microsoft Exam Vouchers
• Certification Bootcamps
• Hosted Labs