Introduction to ML.NET

on YouTube ↗01h 04m

" summary

ML.NET is a .NET-first ML framework (open source, cross‑platform) with TensorFlow and ONNX interop, model-as-zip persistence and a code-first API; it ships around 0.5 release and notes ~10 years of internal Microsoft use. Demos include a GitHub issue multi‑class classifier (processed ~3,000 rows, delivers 73% micro accuracy), a recommender built on MovieLens (modeled from 20M ratings, 27K movies, 138K users) using factorization machines, and image scoring via Inception/TensorFlow that correctly labels a shark.

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" chapters (31)

1. 0:00Introduction
2. 0:59Machine Learning
3. 5:22Is this a face
4. 5:57How do we build functions
5. 6:16Data
6. 7:03Classification
7. 8:29Cognitive Services
8. 10:30Building Models
9. 12:07Agenda
10. 13:23MLNET
11. 20:56GitHub Issue Classification
12. 21:32MultiClass Classification
13. 22:08Multiple Labels
14. 23:58Console Application
15. 24:27Pipeline
16. 25:47GitHub Issue
17. 26:45Pipeline Example
18. 27:56Supervised Learning
19. 29:28Label
20. 30:18Title
21. 30:41Numeric Vector
22. 31:29Glossary
23. 41:12Review
24. 44:25Favorite movies
25. 45:19Netflix
26. 45:34Population averages
27. 47:10Contentbased filtering
28. 49:50Data set
29. 50:24Factorization
30. 51:12Essence of Machine Learning
31. 51:42Demo

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