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Deep Learning Lab

Descrizione

This course offers an opportunity to acquire practical experience in using TensorFlow to implement feedforward and recurrent neural networks (e.g., long short-term memory networks). Such networks currently achieve state-of-the-art results in many exciting tasks, such as object recognition, speech recognition, language translation, and learning to play games from experience. TensorFlow is an open source library developed by Google, and currently is perhaps the most popular choice among researchers and practitioners. Students will be evaluated through practical assignments.

 

RECOMMENDED COURSES
Machine Learning

 

 

REFERENCES

  • Bishop, C. M. (2006). Pattern Recognition and Machine Learning. Springer. Murphy, K. P. (2012).
  • Machine learning: a probabilistic perspective. MIT Press. Graves, A. (2012).
  • Supervised sequence labelling with recurrent neural networks. Springer. Nielsen, M. (2015).
  • Neural networks and deep learning. Determination Press.

Persone

 

Rauber P.

Docente titolare del corso

Schlag I.

Assistente

Informazioni aggiuntive

Semestre
Autunnale
Anno accademico
2018-2019
ECTS
3
Lingua
Inglese
Offerta formativa
Master of Science in Artificial Intelligence, Corso di base, Corso, 1° anno

Dottorato in Scienze informatiche, Corso a scelta, 2° anno (2 ECTS)

Dottorato in Scienze informatiche, Corso a scelta, 1° anno (2 ECTS)