Introduction to Deep Learning

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Ends on

Introduction to Deep Learning
LECTURER

Elisa Ricci

ORGANIZER/S

University of Trento

CONTENT AND ORGANIZATION

The course aims to provide students with an overview of the main models and applications of deep learning. In particular, the first part of the course will introduce the basic concepts related to deep learning and to the training of artificial neural networks (Backpropagation, Dropout, BatchNorm, …). In the second part, the main types of neural models will be presented. Convolutional Neural Networks, Recurrent Neural Networks, Generative Adversarial Networks, Deep Reinforcement Learning will be introduced. In the final part of the course some applications of deep learning will be presented in the field of computer vision, robotics and natural language processing. Theoretical discussion will be complemented with lab in Python using open-source deep learning libraries.

LEVEL

Graduate course

COURSE TYPE

Full course

PARTICIPATION TERMS

ECTS 6

SCHEDULE

Spring semester

LANGUAGE

English

Other short courses

2021. 06. 2 Go

Deep Learning 2

2021. 06. 2 Go

Image Processing

2021. 06. 1 Go

Continual Learning

2021. 06. 1 Go

Computer Vision

2021. 06. 1 Go

Machine listening

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