Machine Learning - pros and cons, theory and practice. Follow us on Twitter (@espeo_software) for more!

1. Azure Machine Learning
Michał Jankowski

2. Agenda
Theory ~20 min
Experiment ~40 min
Summary

3. Theory

4. Machine learning
Learning means changes in a system that have adaptive character, so a system may realize the same or similar task in a more
efficient way with every next attempt. - Herbert Simon (1983)
Learning is a constructing and changing the representation of experienced facts. - Ryszard Michalski (1986)
Learning system uses external empirical data in order to create and update foundations for improved activity in the future
when based on similar data. - Donald Michie (1991)
https://pl.wikipedia.org/wiki/Uczenie_maszynowe#Wsp.C3.B3.C5.82czesne_definicje_uczenia_si.C4.99

5. New paradigm
Traditional programming Machine learning

6. Why?
Exponential growth of data (social networks, IoT – Internet of Things) - 44 tryllions of GB will be
generated till 2020
Cheap data storage
Big computing power of personal computers
Real influence on profits
World (and especially human behavior) is based on patterns
In 2013 roku 22% of data was valuable for analysis, but only 5% from that was analyzed. Till 2020
35% of data will be valuable for analysis

7. AzureML from the outside
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8. … and from the inside
Anomaly detection
Classification
Clustering
Regression

9. Learning
Supervised learning Unsupervised learning
age position city salary
19 student W-wa 1500
29 lekarz P-ń 3500
41 sprzedawca P-ń 3100
31 kierowca W-wa 2100
80 emeryt P-ń 1800
15 uczeń W-wa 0
age position city
19 student W-wa
29 lekarz P-ń
41 sprzedawca P-ń
31 kierowca W-wa
80 emeryt P-ń
15 uczeń W-wa

11. How it works?
Number of
customers
Profit
10 500zł
40 2500zł
100 8000zł
150 12000zł
200 17000zł
y = ax + b

13. Experiment

14. Summary

15. Pros :) and cons.. :(
Cloud based (no need for infrastructure)
Web application (no maintenance/management costs)
No access to trained model
Many algorithms and ease of use
Possibility to use R and Python scripts
Accessibility via Webservices

16. Pricing

17. Pricing
https://azure.microsoft.com/en-us/pricing/details/machine-learning/