
Create ML pipelines with Azure Machine Learning Studio's Python SDK for efficient data science and machine learning workflows on Azure.

Explore Azure ML's Model Catalogue and create an Online Inference EndPoint for Foundation QA HuggingFace model predictions. Gain hands-on experience with Azure ML studio and machine learning deployment.

Create and deploy a multi-component pipeline with Azure ML, including component registration, data management, and Batch Endpoint setup for efficient machine learning workflows.

Fine-tune a BERT foundation model using Azure Machine Learning Studio for enhanced natural language processing capabilities.

Fine-tune LLM for document classification using Azure ML Studio's Python SDK. Learn to adapt Llama2, Mistral, or other models for text classification tasks.

Explore Azure AI and OpenAI Studio, learn Python SDK usage, and discover practical examples for machine learning and data science applications.

Deploy ONNX models to Azure ML Managed Endpoints (AKS) for efficient inference. Learn step-by-step process using Python SDK v2 to optimize machine learning operations.

Deploy a Vision Transformer model for CPU inference on Azure Kubernetes Service using ONNX format and Azure ML SDK v2. Learn to create managed endpoints in Azure ML Studio.

Aprenda a implementar un modelo ViViT en ONNX para inferencia en CPU utilizando Azure Kubernetes Services y onnxruntime con Python SDK v2.

Explore IoT-enabled biometric security using Azure Cloud, integrating CCTV cameras, Cognitive Services, and Machine Learning for advanced physical access control and intrusion detection.

Explore time series data processing, analytics, and predictions using Azure services like Time Series Insights, Machine Learning, and Data Explorer for IoT scenarios and data-driven solutions.

Explore how AI combats counterfeit products using Azure services. Learn to build, manage, and deploy AI solutions for identifying fakes with just a smartphone picture.

Explore practical approaches to responsible AI and learn how open-source and cloud-integrated capabilities empower data scientists to understand and improve ML models ethically.

Develop ML applications using Azure Machine Learning Studio Python SDK v2. Train models and publish to Azure ML model repository.

Master distributed training techniques for custom LLMs using Azure AI infrastructure, focusing on performance optimization, scalability, and efficient deployment with ND H100 and H200 series.

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