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Build, Train, and Deploy Models with Azure Machine Learning

Explore sessions on the entire ML lifecycle. Find practical guides on using Azure ML Studio, the Python SDK, managing datasets, and implementing MLOps pipelines.

Matching moments

Introducing the Azure Machine Learning platform and workspace
03:38 MIN

Introducing the Azure Machine Learning platform and workspace

Introduction to Azure Machine Learning

Navigating the complex landscape of AI cloud services
04:31 MIN

Navigating the complex landscape of AI cloud services

Reference Architecture of AI in the Cloud

Forecasting future demand with integrated ML notebooks
02:00 MIN

Forecasting future demand with integrated ML notebooks

Data Analytics with Microsoft Fabric: End-to-End Use Case with Data Agents

Using Azure AI for model selection and benchmarking
03:08 MIN

Using Azure AI for model selection and benchmarking

From Traction to Production: Maturing your LLMOps step by step

Key takeaways and recommended learning resources
08:34 MIN

Key takeaways and recommended learning resources

Introduction to Azure Machine Learning

Building models visually with the drag-and-drop designer
06:23 MIN

Building models visually with the drag-and-drop designer

Introduction to Azure Machine Learning

Training, evaluating, and debugging the ML model
03:27 MIN

Training, evaluating, and debugging the ML model

Leverage Cloud Computing Benefits with Serverless Multi-Cloud ML

Introducing the Azure AI platform for end-to-end LLMOps
04:59 MIN

Introducing the Azure AI platform for end-to-end LLMOps

From Traction to Production: Maturing your LLMOps step by step

Exploring the capabilities of Azure AI Foundry
03:00 MIN

Exploring the capabilities of Azure AI Foundry

Azure AI Foundry for Developers: Open Tools, Scalable Agents, Real Impact

Selecting and deploying models using Azure AI Foundry
03:15 MIN

Selecting and deploying models using Azure AI Foundry

From Traction to Production: Maturing your GenAIOps step by step

Monitoring GenAI applications with Azure observability tools
01:10 MIN

Monitoring GenAI applications with Azure observability tools

From Traction to Production: Maturing your GenAIOps step by step

Leveraging evolving hyperscaler AI solutions
00:49 MIN

Leveraging evolving hyperscaler AI solutions

Should we build Generative AI into our existing software?

Solving developer challenges with Azure AI Foundry
02:23 MIN

Solving developer challenges with Azure AI Foundry

Agentic AI - From Theory to Practice: Developing Multi-Agent AI Systems on Azure

Comparing the LLM strategies of major cloud providers
01:39 MIN

Comparing the LLM strategies of major cloud providers

Exploring LLMs across clouds

Exploring the Azure AI Foundry Agent Service
01:26 MIN

Exploring the Azure AI Foundry Agent Service

Agentic AI - From Theory to Practice: Developing Multi-Agent AI Systems on Azure

Setting up your Azure ML Studio and compute resources
07:17 MIN

Setting up your Azure ML Studio and compute resources

Introduction to Azure Machine Learning

Q&A: When and how to use AutoML in your projects
02:03 MIN

Q&A: When and how to use AutoML in your projects

Data Science in Retail

Exploring Microsoft's Azure AI services and tools
09:22 MIN

Exploring Microsoft's Azure AI services and tools

Inside the AI Revolution: How Microsoft is Empowering the World to Achieve More

How the Azure AI platform supports the GenAIOps journey
04:27 MIN

How the Azure AI platform supports the GenAIOps journey

From Traction to Production: Maturing your GenAIOps step by step

Automating the data pipeline with multi-cloud services
04:09 MIN

Automating the data pipeline with multi-cloud services

Leverage Cloud Computing Benefits with Serverless Multi-Cloud ML

Deploying and monitoring flows with Azure AI tools
04:30 MIN

Deploying and monitoring flows with Azure AI tools

From Traction to Production: Maturing your LLMOps step by step

Demo: Building an ML model with the AutoAI experiment
05:47 MIN

Demo: Building an ML model with the AutoAI experiment

Data Fabric in Action - How to enhance a Stock Trading App with ML and Data Virtualization

Automating AI quality evaluation in DevOps pipelines
04:53 MIN

Automating AI quality evaluation in DevOps pipelines

Azure AI Foundry for Developers: Open Tools, Scalable Agents, Real Impact

Applying machine learning in the automotive industry
02:06 MIN

Applying machine learning in the automotive industry

Getting Started with Machine Learning

An overview of the three-layer AWS AI/ML stack
02:51 MIN

An overview of the three-layer AWS AI/ML stack

Machine Learning for Software Developers (and Knitters)

Building a cloud architecture for large-scale ML
03:03 MIN

Building a cloud architecture for large-scale ML

Geometric deep learning for drug discovery

Understanding the core components of a GenAI stack
04:45 MIN

Understanding the core components of a GenAI stack

Building Products in the era of GenAI

The challenge of operationalizing production machine learning systems
02:47 MIN

The challenge of operationalizing production machine learning systems

Model Governance and Explainable AI as tools for legal compliance and risk management

The new workflow for training and deploying models
03:29 MIN

The new workflow for training and deploying models

Using Containers to deploy AI Models across our microscopy platform

Developing models with a code-first approach using notebooks
09:54 MIN

Developing models with a code-first approach using notebooks

Introduction to Azure Machine Learning

Essential cloud services for building AI architectures
04:49 MIN

Essential cloud services for building AI architectures

Reference Architecture of AI in the Cloud

Using AutoML for automated model creation and selection
08:57 MIN

Using AutoML for automated model creation and selection

Introduction to Azure Machine Learning

Demo of a secure medical imaging AI model
03:07 MIN

Demo of a secure medical imaging AI model

This Machine Ends Data Breaches

The production architecture and technology stack for AML AI
03:27 MIN

The production architecture and technology stack for AML AI

Detecting Money Laundering with AI

Getting started with the Azure AI Foundry platform
01:27 MIN

Getting started with the Azure AI Foundry platform

How Mixed Reality, Azure AI and Drones turned me into a Magician?

Accelerating AI and machine learning with Arm C-Cloudy
01:50 MIN

Accelerating AI and machine learning with Arm C-Cloudy

Unleashing the Full Potential of the Arm Architecture – Write Once, Deploy Anywhere

Matching Videos

Introduction to Azure Machine Learning
54:27

Introduction to Azure Machine Learning

Jose Luis Latorre Millas

Machine Learning in ML.NET
1:11:20

Machine Learning in ML.NET

Marco Zamana

Geometric deep learning for drug discovery
42:56

Geometric deep learning for drug discovery

Noah Weber

Leverage Cloud Computing Benefits with Serverless Multi-Cloud ML
39:58

Leverage Cloud Computing Benefits with Serverless Multi-Cloud ML

Linda Mohamed

Making neural networks portable with ONNX
54:49

Making neural networks portable with ONNX

Ron Dagdag

Inside the AI Revolution: How Microsoft is Empowering the World to Achieve More
1:09:49

Inside the AI Revolution: How Microsoft is Empowering the World to Achieve More

Simi Olabisi

Effective Java Strategies and Architectures for Clouds
42:23

Effective Java Strategies and Architectures for Clouds

Adam Bien

Seriously gaming your cloud expertise: from cloud tourist to cloud native
49:47

Seriously gaming your cloud expertise: from cloud tourist to cloud native

Piet van Dongen

Develop AI-powered Applications with OpenAI Embeddings and Azure Search
57:52

Develop AI-powered Applications with OpenAI Embeddings and Azure Search

Rainer Stropek

From Traction to Production: Maturing your LLMOps step by step
41:45

From Traction to Production: Maturing your LLMOps step by step

Maxim Salnikov

Computer Vision from the Edge to the Cloud done easy
48:38

Computer Vision from the Edge to the Cloud done easy

Flo Pachinger

From Syntax to Singularity: AI’s Impact on Developer Roles
58:06

From Syntax to Singularity: AI’s Impact on Developer Roles

Anna Fritsch-Weninger

Building Products in the era of GenAI
59:39

Building Products in the era of GenAI

Julian Joseph

Developing an AI.SDK
38:12

Developing an AI.SDK

Daniel Graff & Andreas Wittmann

The Data Mesh as the end of the Datalake as we know it
37:21

The Data Mesh as the end of the Datalake as we know it

Mario Meir-Huber

Azure AI Foundry for Developers: Open Tools, Scalable Agents, Real Impact
23:33

Azure AI Foundry for Developers: Open Tools, Scalable Agents, Real Impact

Oliver Will

Using Containers to deploy AI Models across our microscopy platform
23:56

Using Containers to deploy AI Models across our microscopy platform

Sebastian Rhode

Data Analytics with Microsoft Fabric: End-to-End Use Case with Data Agents
26:58

Data Analytics with Microsoft Fabric: End-to-End Use Case with Data Agents

Dr. Alexander Wachtel & Hanna Schwab

Optimizing your AI/ML workloads for sustainability
46:31

Optimizing your AI/ML workloads for sustainability

Sohan Maheshwar

How Machine Learning is turning the Automotive Industry upside down
26:55

How Machine Learning is turning the Automotive Industry upside down

Jan Zawadzki

Exploring LLMs across clouds
28:38

Exploring LLMs across clouds

Tomislav Tipurić

Deployed ML models need your feedback too
37:24

Deployed ML models need your feedback too

David Mosen

Alibaba Big Data and Machine Learning Technology
43:57

Alibaba Big Data and Machine Learning Technology

Dr. Qiyang Duan

Coffee with Developers - Maria Apazoglou
34:48

Coffee with Developers - Maria Apazoglou

Maria Apazoglou

Reference Architecture of AI in the Cloud
27:57

Reference Architecture of AI in the Cloud

Radu Vunvulea

Data Fabric in Action - How to enhance a Stock Trading App with ML and Data Virtualization
45:58

Data Fabric in Action - How to enhance a Stock Trading App with ML and Data Virtualization

Andreas Christian

From Traction to Production: Maturing your GenAIOps step by step
25:27

From Traction to Production: Maturing your GenAIOps step by step

Maxim Salnikov

Practical AI with Machine Learning for Observability in Netdata
25:32

Practical AI with Machine Learning for Observability in Netdata

Costa

The state of MLOps - machine learning in production at enterprise scale
47:19

The state of MLOps - machine learning in production at enterprise scale

Bas Geerdink 

Detecting Money Laundering with AI
29:37

Detecting Money Laundering with AI

Stefan Donsa & Lukas Alber

Intelligent Automation using Machine Learning
2:11:02

Intelligent Automation using Machine Learning

Boris Krumrey & Andreas Palfi & Radu Pruna

Agentic AI - From Theory to Practice: Developing Multi-Agent AI Systems on Azure
26:35

Agentic AI - From Theory to Practice: Developing Multi-Agent AI Systems on Azure

Ricardo

Self-Hosted LLMs: From Zero to Inference
30:04

Self-Hosted LLMs: From Zero to Inference

Roberto Carratalá & Cedric Clyburn

How to Avoid LLM Pitfalls - Mete Atamel and Guillaume Laforge
42:26

How to Avoid LLM Pitfalls - Mete Atamel and Guillaume Laforge

Meta Atamel & Guillaume Laforge

Is my AI alive but brain-dead? How monitoring can tell you if your machine learning stack is still performing
48:07

Is my AI alive but brain-dead? How monitoring can tell you if your machine learning stack is still performing

Lina Weichbrodt

Remote Driving on Plant Grounds with State-of-the-Art Cloud Technologies
48:54

Remote Driving on Plant Grounds with State-of-the-Art Cloud Technologies

Oliver Zimmert