MLCC@Padova - Scuola Galileiana
Machine Learning Crash Course

Course at a Glance

This year MLCC will be hosted and organized by Scuola Galileiana at university of Padova.

Understanding how intelligence works and how it can be emulated in machines is an age old dream and arguably one of the biggest challenges in modern science. Learning, with its principles and computational implementations, is at the very core of this endeavor. Recently, for the first time, we have been able to develop artificial intelligence systems able to solve complex tasks considered out of reach for decades. Modern cameras recognize faces, and smart phones voice commands, cars can see and detect pedestrians and ATM machines automatically read checks. In most cases at the root of these success stories there are machine learning algorithms, that is softwares that are trained rather than programmed to solve a task.



This course provides an introduction to the fundamental methods at the core of modern Machine Learning. It covers foundations as well as essential algorithms. Classes on theoretical and algorithmic aspects are complemented by practical lab sessions. The course started in 2013 has seen an increasing national and international attendance over the years with a peak of over 150 participants in 2015.



Related courses:

Basic Info

Venue

Scuola Galileiana di Padova


Instructors

Lorenzo Rosasco

Università di Genova
Istituto Italiano di Tecnologia
Massachusetts Institute of Technology

lorenzo (dot) rosasco (at) unige (dot) it

Marco Zanetti

University of Padova

marco (dot) zanetti (at) unipd (dot) com

Teaching Assistants

Gian Maria Marconi

Istituto Italiano di Tecnologia

gianmaria (dot) marconi (at) iit (dot) it



Syllabus

CLASS DAY TIME SUBJECT FILES
127/0213:30-15:00Introduction to Machine Learning
227/0215:30-17:00Local Methods and Model Selection
328/0213:30-15:00Regularization Networks I: Linear Models
428/0215:30-17:00Regularization Networks I: Kernels
501/0314:00-16:30Laboratory 1: Local Methods for Classification
602/0314:00-16:30Laboratory 2: Regularization Networks
7TBATBADimensionality Reduction and PCA
8TBATBAVariable Selection and Sparsity
9TBATBALaboratory 3: PCA and Sparsity
10TBATBAClustering
10TBATBALaboratory 4: Clustering
11TBATBAData Representation: Deep Learning

Organizers

Marco Zanetti

University of Padova

marco (dot) zanetti (at) unipd (dot) com

Lorenzo Rosasco

Università di Genova
(also Istituto Italiano di Tecnologia and Massachusetts Institute of Technology)

lorenzo (dot) rosasco (at) unige (dot) it

Gian Maria Marconi

Istituto Italiano di Tecnologia

gianmaria (dot) marconi (at) iit (dot) it