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Overview
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This course demonstrates how to build real-time object detection solutions in .NET with ML.NET Model Builder. It covers image labeling, model training, experimentation, and integrating generated code and models into applications.
Syllabus
Introduction
Agenda
Why AI
ML NET
Why ML NET
ML NET Possibilities
ML NET Tools
Machine Learning Workflow
Question Time
ML NET CLI
Demo
Beyond Sentiment Analysis
Model Builder
Object Detection
Visual Object Tag Tool
Create Project
ML NET Model Builder
Running the Experiment
How long does it take
Magic
Testing
Code
Model
Model Folder
Taught by
NDC Conferences