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Computer Engineering - Machine Learning

Machine Learning


Synthetic program:
Questo corso fornisce un'introduzione a una sottoarea dell'Intelligenza Artificiale, nota come Machine Learning. Il Machine Learning studia lo sviluppo di programmi che apprendono dall'esperienza. Mentre l'Intelligenza Artificiale si concentra sulla rappresentazione della conoscenza e gli algoritmi per ragionare su tale conoscenza, le tecniche di Machine Learning hanno l'obiettivo di elaborare dati relativi a un certo problema per estrarre conoscenza che verrà utilizzata per risolvere problemi analoghi a quello osservato. Questo corso fornisce le basi teoriche e metodologiche delle tecniche di machine learning e degli algoritmi utilizzati in diversi campi applicativi, tra cui Finanza, Robotica, Agenti autonomi, Bioinformatica, Sistemi di raccomandazione, Social Networks, ecc.

 

Lecture Notes

Complete course:

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Digital notes Complete course notes 2020/2021
Digital notes Complete course notes 2017/2018

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Exercises

Complete course:

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Divided by topic:

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Digital notes 1 - Introduction to Matlab 2015/2016
Digital notes 10 - Reinforcement Learning 2016/2017
Digital notes 2 - Introduction to statistics 2015/2016
Digital notes 3 - Linear regression 2016/2017
Digital notes 4 - Linear classification 2016/2017
Digital notes 5 - Bias Variance Dilemma 2016/2017
Digital notes 6 - Kernel methods 2016/2017
Digital notes 7 - Support vector machines 2016/2017
Digital notes 8 - Markov Decision Processes 2016/2017
Digital notes 9 - Multi-Armed Bandit 2016/2017

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Exams

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Full exam:

Type Date
Text 11/09/2018
Text 04/07/2018
Text 19/06/2018
Text 12/02/2018
Text 22/01/2018
Text 06/07/2017
Text 07/02/2017
Text 26/09/2016
Text 19/07/2016
Text 07/07/2016
Text 28/06/2016

Oral exam:

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Multiple choice test:

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Other

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Collections of notes, exercises or exams:

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Live

Quick daily notes, exercises and audio recordings. Files will be approved on priority but deleted after 365 days. 2 points will be assigned by default.

Quick contents:

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