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AI Product Manager: Plan, Prioritize, and Pitch AI Products
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This talk shows developers how to build a machine learning model with ML.NET Model Builder, refine it using basic data science, and generate code for applications. It also covers training, evaluation, prediction, and troubleshooting.
Syllabus
Introduction
Agenda
MLNET
What is Machine Learning
ML Operations
What is the process
How do we get started
Caveats
MLNET Model Builder
MLNET Trainer
MLNET Model Builder Preview
Data
Demo
Getting started
When to start training
Model Builder
Evaluation
Remove Expenses
New Projects
Prediction Engine
Troubleshooting
Summary
Taught by
NDC Conferences