Data Science
IS EATING THE WORLD
by mart van de ven of droste
Data Science
is
creative
problem solving
with
data
as the
raw
material
y = f(x) + \epsilon
\text{Data Science vs Data Analysis}
\text{Data Science vs Data Engineering}
Data engineers essentially
data for their evaluations and
experiments.
easily retrieve the needed
analyst or data scientist to
lay the groundwork for a data
\text{Data Science vs Machine Learning}
Machine Learning automates modeling. Using
algorithms that iteratively learn from data,
ML allows computers to surface relationships
without explicitly telling them what to look.
DATA DRIVEN EXPERIENCES
\text{Example: Waze}
Text
\text{Level 1: Data Collection}
Text
\text{Level 2: Data Application}
\text{Level 3: Data Driven Experience}
In a world where software builds itself,
computers will only be limited
by the data they can or cannot access,
not by their algorithms.
software builds itself,
Our Stack is Open
Data Storage
Data Pipelines
Machine Learning
Analysis
Visualisation
Our Stack is Open
Our Stack is Open
SQL,HDFS,Cassandra
Airflow,Luigi,OpenRefine
SciKit,MLLib,TensorFlow Pandas,R,
GGplot,Bokeh,Plotly
\text{supervised} \space \text{vs} \space \text{unsupervised}
\text{classification} \space \text{vs} \space \text{estimation}
\text{Example : Automated Risk Credit Management}
\text{Example : Payments Analytics}
\text{Example : Customer Segmentation}
\text{Cultivating a Data Science Team}
A Data Scientist is a
better programmer than
most statisticians, and
a better statistician
than most programmers.
\text{Code Demo : Predicting P2P Loan Interest Rates}
Level 2 : GA HK
Level 1 : DS Prologue
Level 3 : OSDS Masters
LEARNING DATA SCIENCE
