This course aims to teach learners how to implement real-time object detection using ML.NET. The learning outcomes include understanding the importance of computer vision in various industries, learning to use ML.NET Model Builder for object detection, and exploring tools for labeling images. The course teaches skills such as implementing object detection, using ML.NET tools, and understanding the machine learning workflow. The teaching method involves a combination of theoretical explanations, demonstrations, and practical examples. The intended audience for this course includes individuals interested in staying in the .NET world and solving complex computer vision problems.
Beyond Sentiment Analysis - Real Time Object Detection with ML NET
Overview
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
