Machine Learning Simplified for Developers with ML.NET

Explore machine learning from a developer's perspective in this 59-minute conference talk. Learn how to prototype solutions using ML.NET Model Builder, apply basic data science concepts to improve models, and generate code for practical applications. Discover the process of creating custom machine learning models and implementing them in your projects. Gain insights into ML operations, data preparation, model training, evaluation, and troubleshooting. By the end of the talk, acquire the skills to develop and integrate machine learning solutions into your applications with minimal complexity.

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