AI Mastery 201: Elevating Your Workflow with Advanced LLM Techniques
Machine Learning Simplified for Developers with ML.NET (Global AI Bootcamp 2019)
1. THANK YOU TO ALL THE SPONSORS
@Glob_AIBootcamp #GlobalAIBootcampBrisbane
Global Sponsors
Local Sponsors
2. Global AI Bootcamp 2019
Machine Learning
Simplified for Developers with
ML.NET
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3. Senior Software Architect at SSW
Jernej Kavka (JK)
@Jernej_kavka
github.com/jernejk
jkdev.me
linkedin.com/in/jernejkavka/
.NET Core and EF Core dev at day
Cognitive Services and ML.NET dev at night
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11. ML.NET
• MS machine learning SDK that works offline
• Simple yet powerful
• Used in PowerBI, Outlook, Visual Studio…
• Support major ML models
• TensorFlow
• ONNX
• Awesome samples on GitHub
• https://github.com/dotnet/machinelearning-samples
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12. My goal
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POS AUTHORISATION DOTNETFOUNDATION
ORG REDMOND WA Card Used 0082
COFFEE 7 Melbourne
Audible Australia Melbourne
Investment
Food & Drink
Education
15. Machine Learning process
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Improve
Data
Training data Model
ML Training
Desktop and mobile
Web
IoT
Feedback
Deploy
Usage
22. How do I start?
• Start with a scenario
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23. Scenarios
• Is Tweet positive?
• Binary classification
• Categorize bank transactions
• Multi-class classification
• House price predictions
• Regression
• Product recommendation
• Clustering
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24. Caveats
• ML won’t magically solve your problem
• Understand your data
• Guide ML toward right solution
• Start with something simple (classification)
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28. Build model (acquire knowledge)
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Training data Model
ML Training
29. Build model (acquire knowledge)
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Training data Model
ML Training
30. ML.NET Model Builder
• Wizard built on top of ML.NET SDK
• Picks best trainer for given scenario and data
• Can be different one as the data changes over time
• Allows quick prototyping
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32. Let’s do it
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POS AUTHORISATION DOTNETFOUNDATION
ORG REDMOND WA Card Used 0082
COFFEE 7 Melbourne
Audible Australia Melbourne
Investment
Food & Drink
Education
33. Training data preparation
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Manual classification
34. Training data (CSV)
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36. Summary
• Import CSV file
• Tweak columns to get better results
• Generate project with ML
• Tweaking generated code
• Minor issues with small datasets (100+ rows)
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