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About Machine Learning
🤖📓
Mario Gintili
What?

How?

In the wild
What?
40%
40%
20%
Artificial Intelligence Programming Statistical Analysis
How? Implementations
- The computing “muscle” required to do ML became
available for commercial use

- Algorithms - aka the though bit - became publicly
accessible through OSS projects

- The applications are endless - ML has a place in
most businesses nowadays
How? Applications
This is just a over simplified subset of what’s actually happening.
Done exclusively for the purposes of this presentation🌚 🌚
Age Gender Height(m) Body fat %
20 Male 1.79 19
34 Female 1.67 29
Features
Predictions
In the wild
- Cancer prediction & prognosis[1]


- Tuning trading algorithms 

- Content tailoring
[1] http://www.sciencedirect.com/science/article/pii/S2001037014000464
In the wild - Content based platforms
Can be dynamically fabricated
by classifying content
Thank you
Mario Gintili
https://github.com/mariogintili/machine-learnist
$

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