Slides used during the session on Machine Learning .Net for the C# Community web meetup.

1. Bruno Capuano
Innovation Lead @Avanade
@elbruno | http://elbruno.com

2. DESKTOP CLOUDWEB MOBILE ML
.NET
Your platform for building anything
IoTGAMING

3. “It has exquisite buttons …
with long sleeves …works for
casual as well as business
settings”{f(x) {f(x)

4. f(x)
Model
Machine Learning creates a
Using this data

5. Is this A or B? How much? How many? How is this organized?
Regression ClusteringClassification

6. MakeMagicHappen();
https://www.microsoft.com/net/learn/apps/machine
-learning-and-ai

7. How .NET team
uses ML

8. Easy / Less Control Full Control / Harder
Vision Speech Language
Knowledge SearchLabs
TextAnalyticsAPI client = new TextAnalyticsAPI();
client.AzureRegion = AzureRegions.Westus;
client.SubscriptionKey = "1bf33391DeadFish";
client.Sentiment(
new MultiLanguageBatchInput(
new List<MultiLanguageInput>()
{
new MultiLanguageInput("en","0",
"This vacuum cleaner sucks so much dirt")
}));
e.g. Sentiment Analysis using Azure Cognitive Services
9% positive
Pre-built ML Models (Azure Cognitive Services)

9. Easy / Less Control
Full Control / Harder
Prepare Your Data Build & Train Run
Build your own (custom) ML Models

10. Less Control / Easy
Existing Solutions
Build your own (custom) ML Models

11. 02 WHAT IS ML.NET?
ML.NET is a
framework first

12. ML.NET is a framework first

13. 03 WHAT IS ML.NET?
ML.NET has been
proven in large scale
Microsoft products

14. ML.NET Usage at Microsoft
+ more!
Windows 10
Power Point
Excel
Bing Ads

15. 04 WHAT IS ML.NET?
ML.NET is
Open Source
& Cross-Platform

16. Microsoft Confidential
Proven & Extensible Open Source
https://github.com/dotnet/machinelearning
Build your own
Supported on Windows, Linux, and macOS
Developer Focused
ML.NET 0.3.0 (Preview)
Machine Learning framework made for .NET developers

17. MakeMagicHappen();
https://www.microsoft.com/net/learn/apps/machine
-learning-and-ai

20. Load Data Extract Features Train Model Evaluate Model Model consumption
labels + plain text labels + feature vectors model

21. Load Data Extract Features Train Model Evaluate Model Model consumption
labels + plain text labels + feature vectors
Enter...
in ML.NETLearningPipelines!
model

22. Load Data Extract Features Train Model Evaluate Model Model consumption

23. MakeMagicHappen();
https://www.microsoft.com/net/learn/apps/machine
-learning-and-ai

26. Bruno Capuano
Innovation Lead @Avanade
@elbruno | http://elbruno.com