Machine Learning introduction | Mario Gintili
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Machine learning involves using algorithms to find patterns in data to make predictions or decisions without being explicitly programmed. The document discusses that machine learning uses artificial intelligence, statistical analysis, and programming to implement algorithms using open source software projects. It then provides examples of machine learning applications like cancer prediction, tuning trading algorithms, content tailoring, and dynamically generating content for platforms.
![In the wild
- Cancer prediction & prognosis[1]
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- Tuning trading algorithms ?
- Content tailoring
[1] http://www.sciencedirect.com/science/article/pii/S2001037014000464](https://image.slidesharecdn.com/machine-learning-mario-gintili-160630132810/85/Machine-Learning-introduction-Mario-Gintili-6-320.jpg)
Machine Learning introduction | Mario Gintili
- 1. About Machine Learning ?? Mario Gintili
- 3. What? 40% 40% 20% Arti?cial Intelligence Programming Statistical Analysis
- 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. How? Applications This is just a over simpli?ed 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. In the wild - Cancer prediction & prognosis[1] ? - Tuning trading algorithms ? - Content tailoring [1] http://www.sciencedirect.com/science/article/pii/S2001037014000464
- 7. In the wild - Content based platforms Can be dynamically fabricated by classifying content