Syväoppiminen (AVOIN YO)

5 op, Lukuvuosi 2024-2025, 521153S
Upon completion of the course, the student understands the fundamentals of deep learning

Ilmoittautumisaika

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Järjestämistapa

Lähiopinnot
Itsenäinen opiskelu

Toteutusaika

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Ilmoittautuminen

Ilmoittautuminen avoinna
Ilmoittautuminen päättyy .
Ilmoittaudu

Koulutuksen tiedot

The introductory course on deep learning presents the basic concepts, theory, algorithms and models, and provides hands-on experience on implementing, training and utilizing deep neural networks. The topics covered include: linear and logistic regression, loss functions, fully-connected feed-forward neural networks, backpropagation, gradient descent, convolutional neural networks (CNNs), recurrent neural networks (RNNs), attention (including transformers and vision transformers), generative adversarial networks (GANs), and practical tips for training and utilizing deep neural networks. Various applications of deep learning in fundamental computer vision tasks, such as image classification, object detection and segmentation, are also presented. Finally, limitations, recent progress and new frontiers of deep learning are also discussed.

Koulutusmuoto

Jatkuva oppiminen
Avoin yliopisto-opetus

Lukuvuosi

Lukuvuosi 2024-2025

Koulutusala

Tietojenkäsittely ja tietoliikenne

Opetuskieli

englanti

Opetuksen järjestäjä

Oulun yliopisto

Sijainti

Oulu

Osallistujien enimmäismäärä

10

Esitietovaatimukset

Basic engineering mathematics, especially knowledge of probability, statistics and linear algebra. Basic Python programming skills are highly recommended, such as 521141P Elementary programming course. Completion of the courses 521289S Machine Learning and 521467A Digital Image Processing are very beneficial but not a prerequisite.

Yhteystiedot

Opinto-ohjaus

avoin.yliopisto (at) oulu.fi
Viimeksi päivitetty: 3.7.2024