Try:

ONNX: Interoperable AI Models and High-Performance Inference

Learn to convert models from any framework, like PyTorch or TensorFlow, to the ONNX format. Use the ONNX Runtime to deploy and accelerate inference on diverse hardware.

Matching moments

Understanding the ONNX format for model interoperability
01:34 MIN

Understanding the ONNX format for model interoperability

Introduction to Azure Machine Learning

Understanding ONNX as a portable format for ML models
06:14 MIN

Understanding ONNX as a portable format for ML models

Making neural networks portable with ONNX

Consuming an ONNX model in a .NET console application
24:48 MIN

Consuming an ONNX model in a .NET console application

Machine Learning in ML.NET

Using ONNX Runtime for lightweight model inference
02:50 MIN

Using ONNX Runtime for lightweight model inference

Serverless deployment of (large) NLP models

When to use ONNX for your machine learning projects
02:26 MIN

When to use ONNX for your machine learning projects

Making neural networks portable with ONNX

Deploying the trained model as an inference service
03:58 MIN

Deploying the trained model as an inference service

From Code to Motion: Building an Autonomous Hat-Hunting Robot with Kubernetes & ML

Deploying ML models as a web service with Ktor
04:26 MIN

Deploying ML models as a web service with Ktor

The best of both worlds: Combining Python and Kotlin for Machine Learning

Using data management and open source tools for MLOps
02:18 MIN

Using data management and open source tools for MLOps

MLOps - What’s the deal behind it?

Building a universal data selection framework
05:10 MIN

Building a universal data selection framework

Intelligent Data Selection for Continual Learning of AI Functions

Comparing platform-dependent and independent model deployment strategies
01:02 MIN

Comparing platform-dependent and independent model deployment strategies

Developing an AI.SDK

Deploying models with the high-performance ONNX Runtime
07:20 MIN

Deploying models with the high-performance ONNX Runtime

Making neural networks portable with ONNX

Training an object detection model with Azure Custom Vision
05:58 MIN

Training an object detection model with Azure Custom Vision

Machine Learning in ML.NET

Key takeaways for deploying NLP models serverlessly
02:58 MIN

Key takeaways for deploying NLP models serverlessly

Serverless deployment of (large) NLP models

Demo of fine-tuning a model with custom data
02:52 MIN

Demo of fine-tuning a model with custom data

Developer Experience, Platform Engineering and AI powered Apps

Building neural networks with the Kotlin DL library
02:53 MIN

Building neural networks with the Kotlin DL library

The best of both worlds: Combining Python and Kotlin for Machine Learning

Q&A on Kotlin for machine learning
02:25 MIN

Q&A on Kotlin for machine learning

The best of both worlds: Combining Python and Kotlin for Machine Learning

Optimizing ONNX models for mobile and React Native
03:27 MIN

Optimizing ONNX models for mobile and React Native

Making neural networks portable with ONNX

Performing inference in the browser with ONNX Runtime Web
09:27 MIN

Performing inference in the browser with ONNX Runtime Web

Making neural networks portable with ONNX

Four methods for creating or acquiring ONNX models
11:33 MIN

Four methods for creating or acquiring ONNX models

Making neural networks portable with ONNX

Running an ONNX model in a Node.js application
04:01 MIN

Running an ONNX model in a Node.js application

Making neural networks portable with ONNX

Simplifying development with high-level AI frameworks
06:37 MIN

Simplifying development with high-level AI frameworks

Privacy-first in-browser Generative AI web apps: offline-ready, future-proof, standards-based

Navigating the diverse mobile AI framework ecosystem
02:20 MIN

Navigating the diverse mobile AI framework ecosystem

Mobile AI Just Got Faster: What’s Coming for Developers on Arm

Enterprise-grade features like caching and boundary enforcement
04:38 MIN

Enterprise-grade features like caching and boundary enforcement

Nx - the easy choice

Using Nx to manage and scale a frontend monorepo
05:49 MIN

Using Nx to manage and scale a frontend monorepo

Stairway to Heaven - Scaling Frontends the Right Way

How Nx scales from proof of concept to startup
05:01 MIN

How Nx scales from proof of concept to startup

Nx - the easy choice

Addressing common misconceptions about Nx
08:07 MIN

Addressing common misconceptions about Nx

Nx - the easy choice

A practical demonstration of an Nx workspace
07:24 MIN

A practical demonstration of an Nx workspace

Stairway to Heaven - Scaling Frontends the Right Way

Enhancing Angular monorepos with Nx tooling
02:19 MIN

Enhancing Angular monorepos with Nx tooling

Sustainable Angular Architectures with Nx and Strategic Design

Introducing nono for secure AI agent sandboxing
08:55 MIN

Introducing nono for secure AI agent sandboxing

Securing AI Agents from the Ground Up - Luke Hinds

Overcoming initial skepticism about Nx and monorepos
03:09 MIN

Overcoming initial skepticism about Nx and monorepos

Nx - the easy choice

Community-driven development and getting started with nono
02:41 MIN

Community-driven development and getting started with nono

Securing AI Agents from the Ground Up - Luke Hinds

Applying Nexus RPC to build reliable AI agent tools
01:54 MIN

Applying Nexus RPC to build reliable AI agent tools

RPC Reinvented: Asynchronous, Durable, and Agent-Ready

Addressing performance and adoption challenges with OPA
03:07 MIN

Addressing performance and adoption challenges with OPA

OPA for the cloud natives

Speeding up CI builds with Nx affected commands
04:43 MIN

Speeding up CI builds with Nx affected commands

Sustainable Angular Architectures with Nx and Strategic Design

Key takeaways for adopting Nx and monorepos
00:43 MIN

Key takeaways for adopting Nx and monorepos

Nx - the easy choice

Introducing the Open Policy Agent (OPA) and Rego
02:33 MIN

Introducing the Open Policy Agent (OPA) and Rego

OPA for the cloud natives

Matching Videos

Making neural networks portable with ONNX
54:49

Making neural networks portable with ONNX

Ron Dagdag

MLOps - What’s the deal behind it?
29:24

MLOps - What’s the deal behind it?

Nico Axtmann

Privacy-first in-browser Generative AI web apps: offline-ready, future-proof, standards-based
30:13

Privacy-first in-browser Generative AI web apps: offline-ready, future-proof, standards-based

Maxim Salnikov

Intelligent Data Selection for Continual Learning of AI Functions
52:10

Intelligent Data Selection for Continual Learning of AI Functions

Nico Schmidt

Machine Learning in ML.NET
1:11:20

Machine Learning in ML.NET

Marco Zamana

From Code to Motion: Building an Autonomous Hat-Hunting Robot with Kubernetes & ML
30:58

From Code to Motion: Building an Autonomous Hat-Hunting Robot with Kubernetes & ML

Daniel Brintzinger

The best of both worlds: Combining Python and Kotlin for Machine Learning
26:28

The best of both worlds: Combining Python and Kotlin for Machine Learning

Nils Kasseckert

Introduction to Azure Machine Learning
54:27

Introduction to Azure Machine Learning

Jose Luis Latorre Millas

Developing an AI.SDK
38:12

Developing an AI.SDK

Daniel Graff & Andreas Wittmann

Mobile AI Just Got Faster: What’s Coming for Developers on Arm
23:09

Mobile AI Just Got Faster: What’s Coming for Developers on Arm

Gian Marco Iodice

Serverless deployment of (large) NLP models
39:02

Serverless deployment of (large) NLP models

Marek Suppa

WeAreDevelopers LIVE – AI and Privacy, On-Device AI and More
1:00:55

WeAreDevelopers LIVE – AI and Privacy, On-Device AI and More

Chris Heilmann, Daniel Cranney & Tarek Ziadé

Nx - the easy choice
45:39

Nx - the easy choice

Miroslav Jonas

AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment
25:41

AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment

Joy Chatterjee

Lynx: Native for More
31:14

Lynx: Native for More

Xuan Huang

RPC Reinvented: Asynchronous, Durable, and Agent-Ready
18:07

RPC Reinvented: Asynchronous, Durable, and Agent-Ready

Maxim Fateev

From foundation model to hosted AI solution in minutes
18:33

From foundation model to hosted AI solution in minutes

Kevin Klues

LLMOps-driven fine-tuning, evaluation, and inference with NVIDIA NIM & NeMo Microservices
29:20

LLMOps-driven fine-tuning, evaluation, and inference with NVIDIA NIM & NeMo Microservices

Anshul Jindal

Sustainable Angular Architectures with Nx and Strategic Design
50:57

Sustainable Angular Architectures with Nx and Strategic Design

Manfred Steyer

Code meets connectivity - Developers as the powerhouse of Network API innovation
21:51

Code meets connectivity - Developers as the powerhouse of Network API innovation

Alex Walling

OPA for the cloud natives
26:23

OPA for the cloud natives

Philipp Krenn

Startup Presentation: StorX - Future of Cloud Storage
07:21

Startup Presentation: StorX - Future of Cloud Storage

Murphy John

Securing AI Agents from the Ground Up - Luke Hinds
56:27

Securing AI Agents from the Ground Up - Luke Hinds

Luke Hinds

Prompt API & WebNN: The AI Revolution Right in Your Browser
30:36

Prompt API & WebNN: The AI Revolution Right in Your Browser

Christian Liebel

Adding knowledge to open-source LLMs
25:35

Adding knowledge to open-source LLMs

Sergio Perez & Harshita Seth

Monoskope: Developer Self-Service Across Clusters
31:48

Monoskope: Developer Self-Service Across Clusters

Jan Steffen

How to Create New RxJS Operators
58:15

How to Create New RxJS Operators

Mohammad-Ali A'râbi

Putting the Graph In GraphQL With The Neo4j GraphQL Library
47:48

Putting the Graph In GraphQL With The Neo4j GraphQL Library

William Lyon

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

From Traction to Production: Maturing your GenAIOps step by step

Maxim Salnikov

OP_PUSH_TX and its applications in Bitcoin smart contracts
21:45

OP_PUSH_TX and its applications in Bitcoin smart contracts

Xiaohui Liu

Develop, test and run a communications application in a serverless cloud
16:38

Develop, test and run a communications application in a serverless cloud

Filippos Kyprianou & Maksym Mednikov

Your Next AI Needs 10,000 GPUs. Now What?
29:52

Your Next AI Needs 10,000 GPUs. Now What?

Anshul Jindal & Martin Piercy

Building Better with Nuxt 3
41:22

Building Better with Nuxt 3

Daniel Roe

Unveiling the Magic: Scaling Large Language Models to Serve Millions
31:25

Unveiling the Magic: Scaling Large Language Models to Serve Millions

Patrick Koss

How E.On productionizes its AI model & Implementation of Secure Generative AI.
19:27

How E.On productionizes its AI model & Implementation of Secure Generative AI.

Kapil Gupta

AX is the only Experience that Matters
25:14

AX is the only Experience that Matters

Ivan Burazin