Examples of my work in Machine Learning, Deep Learning, Artificial Intelligence and Natural Language Processing using R, Python and Wolfram Mathematica. Also includes Reinforcement Learning, GeoLocation, Face Recognition and Social Networks.

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All
images,
graphics,
analysis
and
models
presented
here
were
developed
by
me

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I
was
CEO
of
Doux
from
2010
to
2013.
The
clinic
has
a
yearly
revenue
of
2.5
million
BRL.
In
2010
the
business
has
a
debt
of
1
million
BRL
and
monthly
revenue
of
64
thousand
BRL.
I
fired
6
out
of
12
employees,
hired
new
ones
and
did
a
quality
research
with
clients.
I
analyzed
results
of
the
research
and
the
database
(750,000
records)
regarding
demographic
data,
profitability,
purchases
patterns,
cost,
time
spent
in
procedures
and
sales.
I
opted
for
a
value
strategy,
high
service
quality,
moderate
cost
control,
investment
in
digital
strategies
and
fostering
of
word
of
mouth
advertising.
In
the
first
years
profit
increased
100%
and
lots
of
patients
returned
to
the
business.
Then
I
increased
price
by
8%,
defined
goals
for
variable
remuneration
and
more
flexible
payment
options.
Most
part
of
profit
was
reinvested
in
the
business.
I
increased
salary
of
employees
by
20%
and
goals
were
achieved
in
70%
of
time.
Most
employees
received
2
or
3
additional
salaries
due
to
variable
remuneration.
They
also
got
healthcare
and
their
satisfaction
ncreased
quality
offered
to
the
clients.
After
2.5
years,
net
profit
increased
239%,
financial
leverage
decreased
36%,
ROI
increased
206%,
ROE
95%,
EBITDA
98.5%
and
monthly
revenue
became
180
thousand
BRL
(almost
tripled).

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Tracking
tools:
-­‐ Google
Adwords
-­‐ Google
Webmasters
Tools
-­‐ Google
Analytics
-­‐ Google
Search
-­‐ Woorank
-­‐ Locaweb
Control
Panel
-­‐ Internal
reports
-­‐ Database
data
Locaweb Graphics
Daily
Visits
to
Doux
Dermatology
Website
Rubens
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REVENUE
PROFIT

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GOAL

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Tableau database

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Sales
Profit

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Below
I
present
a
model
that
simulates
population
dynamics,
where
we
can
see
number
of
consumers
in
each
class
(satisfaction
levels,
diferente
colors)
and
their
evolution
over
time
(weeks).
The
model
uses
artificial
intelligence
with
autonomous
choices
of
partners
(unsupervised
learning)
and
complex
behavior.
Tempo
t
Tempo
t+23
Consumidores
Estados

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Geolocation
of
sales
in
the
states
Profit/Loss
Analysis

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Patent
of
the
Social
Network
code
I also develop social network models using artificial
intelligence associated to supervised and unsupervised
machine learning, to identify clusters and relevant
customers in a community. This way, marketing efforts can
be easily directed.

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Clusters
inside
community
1
Community
1
(dark
red)
This
model
was
conceived
through
interactions
among
clients.
We
can
see
the
spatial
configuration
of
the
social
network
(social
distance),
connections,
positioning
of
people
of
interest
(red
circles),
communities
(diferente
colors),
clusters
inside
a
coommunity,
people
of
interest’s
connections
and
simulate
future
interactions
following
a
pattern
of
interaction.
Consumer
of
interest

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Social
Network
of
5.000
consumers
Communities
in
different
colors
Consumer
of
interest
(red
dot)

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Pattern
1
Pattern
2
Line
of
pattern
GOAL

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80%
of
Big
data
is
unstructured.
This
is
the
great
challenge
of
businesses
in
the
analysis,
given
that
academic
literature
lacks
a
reliable
way
to
code
and
analyze
this
type
of
data.
I
developed
an
algorithm
that
identifies
keywords,
the
reasoning
of
the
text
and
the
subject
and
I
have
the
research
skills
to
develop
a
new
way
to
code
and
analyze
unstructured
data
via
qualitative
analysis.

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RUBENS
ZIMBRES
rubens.zimbres@eclipso.de
(11)
96750-­‐6962
(11)
3022-­‐6755