This presentation was given by our Lead Data Scientist, Adauto Braz, at Papis.io/latam-2019 sharing some insights about our clustering project using unsupervised learning algorithms such as DBSCAN, K-Means.

1. I know what you did last session:
clustering users with ML

2. About me
in/adauto-braz-687735a0/
Adauto Braz
Data Scientist at Stoodi

3. Data Science doesn’t
have to be cool,
to rule my world.
- Prince

4. Data Science projects don’t
need to use the latest
technology to deliver value.
There are low hanging fruits
everywhere.

5. This is a
platform’s,
platform’s
world.
- James Brown

6. Platforms!

7. WATCH
VIDEOS
ORGANIZE A
STUDY PLAN
WRITE
ESSAYS
SUBMIT
EXERCISES
WATCH LIVE
CLASSES
SEND
DOUBTS

8. Tell me
what you want,
what you
really, really
want.
- Spice Girls

9. What are your objectives?
What data is available?
Is your data consistent and
correct?

10. Aimed for simplicity
Understandable results
Is the data redundant?
● PCA: 2 features could explain >80% of variance

11. Hey I just met you,
And this is crazy
But here’s my data.
Run an algorithm
on it, maybe?
- Carly Rae Jepsen

12. DBSCAN
● Density-based spatial
clustering of
applications with
noise.
● Two parameters:
○ How close the points
have to be?
○ How many points at
least a cluster should
have?

13. Nobody said
clustering
was easy.
No one ever
said it
would be
this hard.
- Coldplay

14. DBSCAN
● Outliers
● Different densities

15. KMeans
● One parameter:
○ How many clusters do
you want to find?
● We don’t know!
○ Tested k from 2 up to
20
● Don’t leave outliers

16. How will I know?
Don’t trust your
feelings.
Clustering can be
deceiving.
- Whitney Houston

17. Inertia
How far are the
points within a
cluster?

18. Silhouette Index
How far are the
points from one
cluster to the
other clusters?

19. Run for different cohorts
Check consistency
You’re done!

20. User
Videos
started
Videos
finished
Studyplans
configured
Exercises
Submitted
Cluster
1 0 0 0 0 A
2 1 0 0 2 B
3 6 4 1 3 C
4 3 1 0 20 D

21. So, so what?
I’m a data star
I got my data moves
And I don’t need you
- Pink

22. We need context to understand the
results
There is value!
Five types of users

23. I wanna scream
and shout
and let it all out
- Britney Spears

24. Turn your insights into knowledge
Translate results to accessible language

25. On the first day after sign up,
there are five main user types:
Ingrid,
the Inactive
Ellen,
the Excited
Alex,
the Athlete
Lucas,
the Lost
Nina,
the Novice
Doesn’t do
anything
Just configures
the study plan
Focus on
exercises:
25+ exercises
Tests a bit of the
platform:
2 Videos and 1
exercise
Really engaged:
study plan +
8 videos +
8 exercises

26. Palpable impact
Data Science team wins!

27. Thank U,
Next
Adauto Braz
adautobraz.neto@gmail.com