Dima Boyko, prezentacja z AImeetup #3, 8.12.2016

1. Data is oxygen for ML
Cracow, 8th December 2016

2. Hello, I’m Dima Boyko
Dima Boyko
Rails developer, Python developer, Data Scientist
Software engineer @inFakt
dima.boyko@infakt.pl
/dimaboyko

3. What computer can do better than human?
What human can do better than computer?

4. What computer can do better than human?
+
What human can do better than computer?

5. ”
Field of study that gives computers the ability to learn
without being explicitly programmed
1959, Arthur Samuel
What computer can do better than human?
+
What human can do better than computer?
Machine learning

6. Machine learning
is not the future

7. Machine learning
ALVIN
YouTube
https://youtu.be/ilP4aPDTBPE?t=39
1992 !

8. Machine learning

9. Boost
ML can boost existing products by
improving quality and usability of some
modules
Unlock
Using ML can unlock new product
use-cases
Machine learning

10. Drawbacks?
Machine learning

11. Drawbacks?
Machine learning
WOW / WTF ratio

12. Data Algorithm Insight
Usage model
Machine learning

13. Data
Usage model
Machine learning

14. Data

15. Using of data

16. Using of data
Red Roof Inn

17. Using of data
2 to 3%
of flights were canceled
Red Roof Inn

18. Using of data
500
daily
Red Roof Inn

19. Using of data
90 000
passengers
Red Roof Inn

20. Using of data
Weather data
Red Roof Inn

21. Using of data
10%
more revenue during season
Red Roof Inn
Results

22. Los Angeles Police Department
Using of data

23. Historical
DATA
Analysis &
Prediction
Reaction
Los Angeles Police Department
Using of data

24. Los Angeles Police Department
Using of data

25. Los Angeles Police Department
Using of data

26. 33%
Less thefts
21%
Less victims
Los Angeles Police Department
Using of data
Results

27. UPS Cargo Delivery
Using of data

28. Using of data
16,9M
Delivered cargos daily
195
Countries around the globe
UPS Cargo Delivery

29. Orion
• Mathematical model for operations research
• Huge processing power in real time
Using of data
UPS Cargo Delivery

30. Using of data
6M
Litres less fuel usage
during the year
13 000
Tons of exhausts
less
UPS Cargo Delivery
+ Faster deliveries
Results

31. inFakt
Automated
Accounting
Using of data

32. ~50 000
Invoices booked monthly by accountants
inFakt Automated Accounting
Using of data

33. AutoAccounting
Brief product history
inFakt Automated Accounting
Using of data

34. AutoAccounting
• Data from last year
• Scikit-learn
• Infrastructure
Classification
15% invoices
95% correct

35. AutoAccounting
• Data from last year
• Infrastructure
Classification
55% invoices
95% correct

36. AutoAccounting
Classification
Keep it simple…

38. 3%
Wrong
Inconsistent
8/10
Human mistake
AutoAccounting

39. ~70%
Invoices booked automatically
AutoAccounting
Results

40. ~70%
Invoices booked automatically
600 / month
Hours saved for creative work
AutoAccounting
Results

41. Know your DATA!

42. Auto
What’s next?

43. Auto
What’s next?
#worldwide #vendor_independent #simple

44. Open Source ?
What’s next?
/OpenAutoX

45. Thanks! Any questions?
Dima Boyko
Software engineer @ inFakt
dima.boyko@infakt.pl
/dimaboyko