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Struttura del corso
- Backprop, modelli modulari
- Modulo logsum
- Rete RBF
- Perdita MAP/MLE
- Trasformazioni spaziali dei parametri
- Modulo Convoluzionale
- Apprendimento basato sul gradiente
- Energia per inferenza
- Obiettivo dell'apprendimento
- PCA, NLL
- Modelli a Variabili Latenti
- LVM probabilistico
- Funzione di perdita
- Riconoscimento della scrittura a mano
Requisiti
Good Fondamenti nell'apprendimento automatico di base. Programming competenze in qualsiasi lingua (idealmente Python/R).
21 ore
Recensioni (7)
The structure from first principles, to case studies, to application.
Margaret Webb - Department of Jobs, Regions, and Precincts
Corso - Introduction to Deep Learning
The deep knowledge of the trainer about the topic.
Sebastian Gorg
Corso - Introduction to Deep Learning
I think that if training would be done in polish it would allow the trainer to share his knowledge more efficient.
Radek
Corso - Introduction to Deep Learning
Exercises after each topic were really helpful, despite there were too complicated at the end. In general, the presented material was very interesting and involving! Exercises with image recognition were great.
Dolby Poland Sp. z o.o.
Corso - Introduction to Deep Learning
Topic. Very interesting!.
Piotr
Corso - Introduction to Deep Learning
Trainers theoretical knowledge and willingness to solve the problems with the participants after the training.
Grzegorz Mianowski
Corso - Introduction to Deep Learning
The topic is very interesting.
