VDMA Vortrag - 2019

1. daenet Gesellschaft für Informationstechnologie mbH
Hanauer Landstr. 204 60314 Frankfurt am Main
Tools für KI/ML
Damir Dobric
daenet GmbH
https://daenet.de

2. https://about.me/damirdobric

3. • Intro
• Patterns in Daten
• Model Training und Model Ausführung
• ML Stack & Tools
• Demos
• Computer Vision als Anwendungen
• Computer Vision als API
• Modelle selbst trainieren mit ML.NET
• Q&A

4. Ihr Partner für digitale Transformation
und Microsoft Azure!
Cloud IoTAI / ML

5. Gegründet 1999
Sitz Frankfurt am Main
30 Mitarbeiter
Unternehmensstandort
und Nearshore
Microsoft
Partner of the
Year Award
2005 & 2010
Starke
Microsoft
Partnerschaft
Gold Cloud Platform
Gold Application Development
Gold Application Integration
Azure Advisors Program
Microsoft Most Valuable Professional
Microsoft Regional Director
Initiative
Mittelstand
BEST OF 2014
INNOVATIONSPREIS-IT
Cloud Computing

7. X Y
1 FALSE
9 TRUE
6 TRUE
4 FALSE
8 TRUE
2 FALSE
7 TRUE
3 FALSE
4 FALSE
5 FALSE
10 TRUE
15 TRUE
12 TRUE
X Y
1 FALSE
2 FALSE
3 FALSE
4 FALSE
4 FALSE
5 FALSE
6 TRUE
7 TRUE
8 TRUE
9 TRUE
10 TRUE
12 TRUE
15 TRUE
https://www.slideshare.net/damirdobric/azure-machine-learning-intro

8. X Y RESULT
----------------------
0.3 0.01 0
0.09 0.09 0
0.11 0.98 0
0.65 0.25 1
0.4 0.82 0
0.25 0.45 1
0.26 0.38 1
0.38 0.6 1
0.48 0.45 1
0.88 0.15 1
0.5 0.88 0
0.6 0.81 0

10. https://github.com/UniversityOfAppliedSciencesFrankfurt/LearningApi/tree/mlp-backpropagation/LearningApi/src/MLAlgorithms/NeuralNetworks/NeuralNet.MLPerceptron/Documentation

11. Model Training Model Run

12. Load Data
Extract
Features
Model
Consumption
Train
Model
Evaluate
Model
Prepare Your Data Build & Train
Run (step 2)
Train (step 1)

13. Fertige Lösungen
Trainierte Modele
als Dienste
Native Algorithmen

14. Windows 10 (Windows Defender)
Power Point (Design Ideas)
Excel (Chart Recommendations)
Bing Ads (Ad Predictions)
+ moreAzure Stream Analytics (Anomaly Detection)

16. https://developers.de/blogs/damir_dobric/archive/2014/12/23/azure-machine-learning-episode-1.aspx

17. https://www.captionbot.ai/Home/Magic?lang=en-US

18. https://westeurope.dev.cognitive.microsoft.com/docs/services/5adf991815e1060e6355ad44/operations/56f91f2e778daf14a49
e1fa/console
https://i.ebayimg.com/images/g/nlMAAOSwAYtWPfzf/s-l300.jpg (adult 20%)
https://cdn.geekwire.com/wp-content/uploads/2018/05/ISm2ws8xojvwbs1000000000.jpg (building)
https://cdn.geekwire.com/wp-content/uploads/2019/05/190514-nasa2-768x521.jpg (multiple personas)
http://www.eroluv.com/thumbs/elv8/37/met-art_LND_211_9.jpg

20. https://aischool.microsoft.com/en-us/home
Real-World Examples

21. • Intro
• Patterns in Daten
• Model Training und Model Ausführung
• ML Stack & Tools
• Demos
• Computer Vision als Anwendungen
• Computer Vision als API
• Modelle selbst trainieren mit ML.NET
• Q&A

22. https://sud.vdma.org/viewer/-/v2article/render/26018603
https://github.com/UniversityOfAppliedSciencesFrankfurt/LearningApi
https://www.slideshare.net/damirdobric/azure-machine-learning-intro
https://aischool.microsoft.com/en-us/home

23. https://about.me/damirdobric
https://www.meetup.com/Azure-Meetup-Frankfurt/

24. © Copyright daenet GmbH. All rights reserved.