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Introduction to ML.NET

NDC Conferences via YouTube

Overview

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This course aims to introduce .NET developers to ML.NET, enabling them to develop and integrate custom AI into existing .NET applications through both code-driven and UI-driven approaches. The course covers scenarios enabled by ML.NET, its vision, and architecture. The individual skills taught include building functions, data classification, using cognitive services, building models, and supervised learning. The teaching method involves a combination of theoretical concepts and practical examples. The course is intended for .NET developers interested in incorporating machine learning capabilities into their applications.

Syllabus

Introduction
Machine Learning
Is this a face
How do we build functions
Data
Classification
Cognitive Services
Building Models
Agenda
MLNET
GitHub Issue Classification
MultiClass Classification
Multiple Labels
Console Application
Pipeline
GitHub Issue
Pipeline Example
Supervised Learning
Label
Title
Numeric Vector
Glossary
Review
Favorite movies
Netflix
Population averages
Contentbased filtering
Data set
Factorization
Essence of Machine Learning
Demo

Taught by

NDC Conferences

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