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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 th...
How? Applications
This is just a over simplified subset of what’s actually happening.
Done exclusively for the purposes of ...
In the wild
- Cancer prediction & prognosis[1]


- Tuning trading algorithms 

- Content tailoring
[1] http://www.scienced...
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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Machine Learning introduction | Mario Gintili

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A small introduction to ML:

What is it?
Why can we use it now?
How does it work? ish

Publié dans : Ingénierie
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Machine Learning introduction | Mario Gintili

  1. 1. About Machine Learning 🤖📓 Mario Gintili
  2. 2. What?
 How?
 In the wild
  3. 3. What? 40% 40% 20% Artificial Intelligence Programming Statistical Analysis
  4. 4. 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
  5. 5. 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
  6. 6. In the wild - Cancer prediction & prognosis[1] 
 - Tuning trading algorithms 
 - Content tailoring [1] http://www.sciencedirect.com/science/article/pii/S2001037014000464
  7. 7. In the wild - Content based platforms Can be dynamically fabricated by classifying content
  8. 8. Thank you Mario Gintili https://github.com/mariogintili/machine-learnist $

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